---------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/cb2257/Desktop/ISQ Replication/isq_blair_schwartz.log
  log type:  text
 opened on:  11 Oct 2023, 23:52:41

. 
. ********************************************************************************
. *                                                                FULL ANALYSIS                                     
>                         *
. ********************************************************************************
. 
. clear all

. 
. ssc install reghdfe, replace
checking reghdfe consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install ftools, replace
checking ftools consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install carryforward, replace
checking carryforward consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install grstyle, replace
checking grstyle consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install mediation, replace
checking mediation consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install outreg2, replace
checking outreg2 consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install coefplot, replace
checking coefplot consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install ppmlhdfe, replace
checking ppmlhdfe consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install cmp, replace
checking cmp consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install ghk2, replace
checking ghk2 consistency and verifying not already installed...
all files already exist and are up to date.

. ssc install boottest, replace
checking boottest consistency and verifying not already installed...
all files already exist and are up to date.

. 
. set more off

. set scheme plotplainblind

. macro drop _all

. est drop _all

. set matsize 800

. set seed 8675309

. 
. ** Set Working Directory
. 
. if c(username) == "christopherblair"{
. global dir "~/Desktop/ISQ Replication"
. global data "${dir}/data"
. global code "${dir}/code"                                                                               
. global results "${dir}/results"                                                                         
. }

. 
. cd "${dir}"
/Users/cb2257

. 
. if c(username) == "cb2257"{
. global dir "~/Desktop/ISQ Replication"
. global data "${dir}/data"
. global code "${dir}/code"                                                                               
. global results "${dir}/results"                                                                         
. }

. 
. cd "${dir}"
/Users/cb2257/Desktop/ISQ Replication

. 
. else if c(username) == "youruser"{
. global dir "~/Desktop/ISQ Replication"
. }

. 
. cd "${dir}"
/Users/cb2257/Desktop/ISQ Replication

. 
. ********************************************************************************
. 
. use "${data}/leader_figure.dta", clear

. est drop _all

. 
. ********************************************************************************
. *                                                                        MAKE FIGURE 1                             
>                         *
. ********************************************************************************
. 
. do "${code}/GenderPeace_Leader.do"

. 
. 
. 
. ***Create Figure 1
. 
. *Read in Figure1.dta
. 
. tw bar average year_count, bcolor(gs9) xlabel(1(1)14) xlabel(1 "1880s" 2 "1890s" 3 "1900s" 4 "1910s" 5 "1920s" 6 "1
> 930s" 7 "1940s" 8 "1950s" 9 "1960s" 10 "1970s" 11 "1980s" 12 "1990s" 13 "2000s" 14 "2010s") ylabel(0 "0" 0.02 "2" 0
> .04 "4" 0.06 "6" 0.08 "8")  ytitle("Average Percentage of Executives Who Are Women", color(black)) xtitle("Year", s
> ize(medsmall)) legend(off) graphregion(color(white) lcolor(white) ilcolor(white)) plotregion(fcolor(white) lcolor(w
> hite) ilcolor(white)) lc(gs11) lpattern(1 1) || fpfit average year_count, lcolor(black) lpatt(dash)

. graph export "${results}/figure1.eps", replace
(file ~/Desktop/ISQ Replication/results/figure1.eps written in EPS format)

. 
. 
. 
. 
. 
.  
. 
end of do-file

. 
. ********************************************************************************
. ********************************************************************************
. ********************************** STUDY 1 *************************************
. ********************************************************************************
. ********************************************************************************
. 
. import delimited "${data}/study1_main.csv", clear
(144 vars, 1,108 obs)

. est drop _all

. 
. ********************************************************************************
. *                                                                CLEAN STUDY 1 DATA                                
>                         *
. ********************************************************************************
. 
. do "${code}/GenderPeace_Cleaning1.do"

. 
. **********CLEAN STUDY 1 DATA***************
. 
. ***Drop Respondents that Failed Attention Check (80% passed)
. keep if disposition1_4=="Neither agree nor disagree"
(178 observations deleted)

. 
. ***SexismOrder (1 = Pre-Treatment; 0 = Post-Treatment)
. gen SexismOrder = 0

. replace SexismOrder = 1 if sexismorder==1
(444 real changes made)

. drop sexismorder

.  
. ***Hostile Sexism (1 = Least Sexist; 6 = Most Sexist)
. gen hostsexism1 = .
(930 missing values generated)

. replace hostsexism1 = 1 if sexism1_before1_1=="Strongly agree" | sexismpost11_1=="Strongly agree"
(165 real changes made)

. replace hostsexism1 = 2 if sexism1_before1_1=="Agree" | sexismpost11_1=="Agree"
(197 real changes made)

. replace hostsexism1 = 3 if sexism1_before1_1=="Somewhat agree" | sexismpost11_1=="Somewhat agree"
(252 real changes made)

. replace hostsexism1 = 4 if sexism1_before1_1=="Somewhat disagree" | sexismpost11_1=="Somewhat disagree"
(133 real changes made)

. replace hostsexism1 = 5 if sexism1_before1_1=="Disagree" | sexismpost11_1=="Disagree"
(59 real changes made)

. replace hostsexism1 = 6 if sexism1_before1_1=="Strongly disagree" | sexismpost11_1=="Strongly disagree"
(58 real changes made)

. 
. gen hostsexism2 = .
(930 missing values generated)

. replace hostsexism2 = 1 if sexism1_before1_2=="Strongly agree" | sexismpost11_2=="Strongly agree"
(96 real changes made)

. replace hostsexism2 = 2 if sexism1_before1_2=="Agree" | sexismpost11_2=="Agree"
(117 real changes made)

. replace hostsexism2 = 3 if sexism1_before1_2=="Somewhat agree" | sexismpost11_2=="Somewhat agree"
(235 real changes made)

. replace hostsexism2 = 4 if sexism1_before1_2=="Somewhat disagree" | sexismpost11_2=="Somewhat disagree"
(203 real changes made)

. replace hostsexism2 = 5 if sexism1_before1_2=="Disagree" | sexismpost11_2=="Disagree"
(102 real changes made)

. replace hostsexism2 = 6 if sexism1_before1_2=="Strongly disagree" | sexismpost11_2=="Strongly disagree"
(111 real changes made)

. 
. gen hostsexism3 = .
(930 missing values generated)

. replace hostsexism3 = 6 if sexism1_before1_3=="Strongly agree" | sexismpost11_3=="Strongly agree"
(52 real changes made)

. replace hostsexism3 = 5 if sexism1_before1_3=="Agree" | sexismpost11_3=="Agree"
(93 real changes made)

. replace hostsexism3 = 4 if sexism1_before1_3=="Somewhat agree" | sexismpost11_3=="Somewhat agree"
(191 real changes made)

. replace hostsexism3 = 3 if sexism1_before1_3=="Somewhat disagree" | sexismpost11_3=="Somewhat disagree"
(199 real changes made)

. replace hostsexism3 = 2 if sexism1_before1_3=="Disagree" | sexismpost11_3=="Disagree"
(149 real changes made)

. replace hostsexism3 = 1 if sexism1_before1_3=="Strongly disagree" | sexismpost11_3=="Strongly disagree"
(180 real changes made)

. 
. gen hostsexism4 = .
(930 missing values generated)

. replace hostsexism4 = 6 if sexism1_before1_4=="Strongly agree" | sexismpost11_4=="Strongly agree"
(52 real changes made)

. replace hostsexism4 = 5 if sexism1_before1_4=="Agree" | sexismpost11_4=="Agree"
(61 real changes made)

. replace hostsexism4 = 4 if sexism1_before1_4=="Somewhat agree" | sexismpost11_4=="Somewhat agree"
(159 real changes made)

. replace hostsexism4 = 3 if sexism1_before1_4=="Somewhat disagree" | sexismpost11_4=="Somewhat disagree"
(189 real changes made)

. replace hostsexism4 = 2 if sexism1_before1_4=="Disagree" | sexismpost11_4=="Disagree"
(183 real changes made)

. replace hostsexism4 = 1 if sexism1_before1_4=="Strongly disagree" | sexismpost11_4=="Strongly disagree"
(220 real changes made)

. 
. gen hostsexism = (hostsexism1 + hostsexism2 + hostsexism3 + hostsexism4) / 4
(66 missing values generated)

. 
. summarize hostsexism, detail 

                         hostsexism
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%            1              1
10%          1.5              1       Obs                 864
25%         2.25              1       Sum of Wgt.         864

50%        3.125                      Mean           3.048322
                        Largest       Std. Dev.      1.032451
75%          3.5              6
90%         4.25              6       Variance       1.065956
95%         4.75              6       Skewness       .0478343
99%         5.75              6       Kurtosis       3.091101

. 
. gen hostsexismIQR = .
(930 missing values generated)

. replace hostsexismIQR = 0 if hostsexism<=2.25
(227 real changes made)

. replace hostsexismIQR = 1 if hostsexism>=3.5
(427 real changes made)

. replace hostsexismIQR = . if hostsexism==.
(66 real changes made, 66 to missing)

. 
. 
. ***Benevolent Sexism (1 = Least Sexist; 6 = Most Sexist)
. *Note: Questions 3 and 4 are negatively correlated with 1 and 2
. gen benevsexism1 = .
(930 missing values generated)

. replace benevsexism1= 6 if sexism1_before1_5=="Strongly agree" | sexismpost11_5=="Strongly agree"
(57 real changes made)

. replace benevsexism1= 5 if sexism1_before1_5=="Agree" | sexismpost11_5=="Agree"
(107 real changes made)

. replace benevsexism1 = 4 if sexism1_before1_5=="Somewhat agree" | sexismpost11_5=="Somewhat agree"
(216 real changes made)

. replace benevsexism1 = 3 if sexism1_before1_5=="Somewhat disagree" | sexismpost11_5=="Somewhat disagree"
(256 real changes made)

. replace benevsexism1 = 2 if sexism1_before1_5=="Disagree" | sexismpost11_5=="Disagree"
(127 real changes made)

. replace benevsexism1 = 1 if sexism1_before1_5=="Strongly disagree" | sexismpost11_5=="Strongly disagree"
(101 real changes made)

. 
. gen benevsexism2 = .
(930 missing values generated)

. replace benevsexism2= 6 if sexism2_before1_1=="Strongly agree" | sexismpost21_1=="Strongly agree"
(62 real changes made)

. replace benevsexism2= 5 if sexism2_before1_1=="Agree" | sexismpost21_1=="Agree"
(78 real changes made)

. replace benevsexism2 = 4 if sexism2_before1_1=="Somewhat agree" | sexismpost21_1=="Somewhat agree"
(287 real changes made)

. replace benevsexism2 = 3 if sexism2_before1_1=="Somewhat disagree" | sexismpost21_1=="Somewhat disagree"
(225 real changes made)

. replace benevsexism2 = 2 if sexism2_before1_1=="Disagree" | sexismpost21_1=="Disagree"
(144 real changes made)

. replace benevsexism2 = 1 if sexism2_before1_1=="Strongly disagree" | sexismpost21_1=="Strongly disagree"
(68 real changes made)

. 
. gen benevsexism3 = .
(930 missing values generated)

. replace benevsexism3= 1 if sexism2_before1_2=="Strongly agree" | sexismpost21_2=="Strongly agree"
(53 real changes made)

. replace benevsexism3= 2 if sexism2_before1_2=="Agree" | sexismpost21_2=="Agree"
(96 real changes made)

. replace benevsexism3 = 3 if sexism2_before1_2=="Somewhat agree" | sexismpost21_2=="Somewhat agree"
(175 real changes made)

. replace benevsexism3 = 4 if sexism2_before1_2=="Somewhat disagree" | sexismpost21_2=="Somewhat disagree"
(243 real changes made)

. replace benevsexism3 = 5 if sexism2_before1_2=="Disagree" | sexismpost21_2=="Disagree"
(141 real changes made)

. replace benevsexism3 = 6 if sexism2_before1_2=="Strongly disagree" | sexismpost21_2=="Strongly disagree"
(156 real changes made)

. 
. gen benevsexism4 = .
(930 missing values generated)

. replace benevsexism4= 1 if sexism2_before1_3=="Strongly agree" | sexismpost21_3=="Strongly agree"
(25 real changes made)

. replace benevsexism4= 2 if sexism2_before1_3=="Agree" | sexismpost21_3=="Agree"
(47 real changes made)

. replace benevsexism4 = 3 if sexism2_before1_3=="Somewhat agree" | sexismpost21_3=="Somewhat agree"
(104 real changes made)

. replace benevsexism4 = 4 if sexism2_before1_3=="Somewhat disagree" | sexismpost21_3=="Somewhat disagree"
(217 real changes made)

. replace benevsexism4 = 5 if sexism2_before1_3=="Disagree" | sexismpost21_3=="Disagree"
(172 real changes made)

. replace benevsexism4 = 6 if sexism2_before1_3=="Strongly disagree" | sexismpost21_3=="Strongly disagree"
(299 real changes made)

. 
. *Since items 3 and 4 are negatively correlated with 1 and 2 going to drop the latter two from the index. Yields a g
> reater reliability measure than reverse coding 3 and 4
. gen benevsexism = (benevsexism1 + benevsexism2) / 2
(66 missing values generated)

. 
. summarize benevsexism, detail

                         benevsexism
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%          1.5              1
10%            2              1       Obs                 864
25%          2.5              1       Sum of Wgt.         864

50%          3.5                      Mean           3.359375
                        Largest       Std. Dev.      1.147906
75%            4              6
90%            5              6       Variance       1.317687
95%          5.5              6       Skewness       .0473469
99%            6              6       Kurtosis       2.804546

. 
. 
. gen benevsexismIQR = .
(930 missing values generated)

. replace benevsexismIQR = 0 if benevsexism<=2.5
(243 real changes made)

. replace benevsexismIQR = 1 if benevsexism>=4
(382 real changes made)

. replace benevsexismIQR = . if benevsexism==.
(66 real changes made, 66 to missing)

. 
. 
. ***Second Order Sexism (1 = Least Sexist; 6 = Most Sexist)
. gen secordersexism_amer_citz = .
(930 missing values generated)

. replace secordersexism_amer_citz = 6 if sexism2_before1_4=="Strongly agree" | sexismpost21_4=="Strongly agree"
(90 real changes made)

. replace secordersexism_amer_citz = 5 if sexism2_before1_4=="Agree" | sexismpost21_4=="Agree"
(139 real changes made)

. replace secordersexism_amer_citz = 4 if sexism2_before1_4=="Somewhat agree" | sexismpost21_4=="Somewhat agree"
(360 real changes made)

. replace secordersexism_amer_citz = 3 if sexism2_before1_4=="Somewhat disagree" | sexismpost21_4=="Somewhat disagree
> "
(168 real changes made)

. replace secordersexism_amer_citz = 2 if sexism2_before1_4=="Disagree" | sexismpost21_4=="Disagree"
(66 real changes made)

. replace secordersexism_amer_citz = 1 if sexism2_before1_4=="Strongly disagree" | sexismpost21_4=="Strongly disagree
> "
(41 real changes made)

. 
. gen secordersexism_for_lead = .
(930 missing values generated)

. replace secordersexism_for_lead = 6 if sexism2_before1_5=="Strongly agree" | sexismpost21_5=="Strongly agree"
(103 real changes made)

. replace secordersexism_for_lead = 5 if sexism2_before1_5=="Agree" | sexismpost21_5=="Agree"
(136 real changes made)

. replace secordersexism_for_lead = 4 if sexism2_before1_5=="Somewhat agree" | sexismpost21_5=="Somewhat agree"
(346 real changes made)

. replace secordersexism_for_lead = 3 if sexism2_before1_5=="Somewhat disagree" | sexismpost21_5=="Somewhat disagree"
(169 real changes made)

. replace secordersexism_for_lead = 2 if sexism2_before1_5=="Disagree" | sexismpost21_5=="Disagree"
(74 real changes made)

. replace secordersexism_for_lead = 1 if sexism2_before1_5=="Strongly disagree" | sexismpost21_5=="Strongly disagree"
(36 real changes made)

. 
. gen secordersexism = (secordersexism_amer_citz + secordersexism_for_lead) / 2 
(66 missing values generated)

. 
. gen secordersexismIQR = .
(930 missing values generated)

. replace secordersexismIQR = 0 if secordersexism<=3.5
(347 real changes made)

. replace secordersexismIQR = 1 if secordersexism>=4.5
(346 real changes made)

. replace secordersexismIQR = . if secordersexism==.
(66 real changes made, 66 to missing)

. 
. 
. ***Militant Assertiveness (1 = Least Hawkish; 6 = Most Hawkish)
. gen hawkish1 = .
(930 missing values generated)

. replace hawkish1 = 5 if disposition1_1=="Strongly agree" 
(114 real changes made)

. replace hawkish1 = 4 if disposition1_1=="Somewhat agree" 
(206 real changes made)

. replace hawkish1 = 3 if disposition1_1=="Neither agree nor disagree" 
(290 real changes made)

. replace hawkish1 = 2 if disposition1_1=="Somewhat disagree" 
(174 real changes made)

. replace hawkish1 = 1 if disposition1_1=="Strongly disagree"
(146 real changes made)

. 
. gen hawkish2 = .
(930 missing values generated)

. replace hawkish2 = 5 if disposition1_2=="Strongly agree" 
(149 real changes made)

. replace hawkish2 = 4 if disposition1_2=="Somewhat agree" 
(393 real changes made)

. replace hawkish2 = 3 if disposition1_2=="Neither agree nor disagree" 
(210 real changes made)

. replace hawkish2 = 2 if disposition1_2=="Somewhat disagree" 
(105 real changes made)

. replace hawkish2 = 1 if disposition1_2=="Strongly disagree"
(73 real changes made)

. 
. gen hawkish3 = .
(930 missing values generated)

. replace hawkish3 = 1 if disposition1_3=="Strongly agree" 
(83 real changes made)

. replace hawkish3 = 2 if disposition1_3=="Somewhat agree" 
(193 real changes made)

. replace hawkish3 = 3 if disposition1_3=="Neither agree nor disagree" 
(319 real changes made)

. replace hawkish3 = 4 if disposition1_3=="Somewhat disagree" 
(220 real changes made)

. replace hawkish3 = 5 if disposition1_3=="Strongly disagree"
(115 real changes made)

. 
. gen hawkish = (hawkish1 + hawkish2 + hawkish3) / 3

. 
. summarize hawkish, detail 

                           hawkish
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%     1.333333              1
10%            2              1       Obs                 930
25%     2.666667              1       Sum of Wgt.         930

50%            3                      Mean           3.178853
                        Largest       Std. Dev.      .8903029
75%     3.666667              5
90%     4.333333              5       Variance       .7926393
95%     4.666667              5       Skewness      -.1857642
99%            5              5       Kurtosis       2.965537

. 
. gen hawkishIQR = .
(930 missing values generated)

. replace hawkishIQR = 0 if hawkish<=2.7
(273 real changes made)

. replace hawkishIQR = 1 if hawkish>=3.6
(321 real changes made)

. replace hawkishIQR = . if hawkish==.
(0 real changes made)

. 
. 
. *Political ID (1 = Most Democrat; 6 = Most Republican)
. gen political_identfication = 1

. replace political_identfication = 2 if political_party==2
(101 real changes made)

. replace political_identfication = 3 if political_party==3 | political_party==6
(109 real changes made)

. replace political_identfication = 4 if political_party==4 | political_party==7
(204 real changes made)

. replace political_identfication = 5 if political_party==8 | political_party==5
(87 real changes made)

. replace political_identfication = 6 if political_party==9
(64 real changes made)

. replace political_identfication = 7 if political_party==10
(145 real changes made)

. 
. gen democratic_respondent = 0

. replace democratic_respondent = 1 if political_identfication<=3
(430 real changes made)

. 
. gen republican_respondent = 0

. replace republican_respondent = 1 if political_identfication>=5
(296 real changes made)

. 
. ***Code Education (1 = Least; 8 = Most; Drop Missing)
. replace education = . if education==-3105 | education==-10
(6 real changes made, 6 to missing)

. 
. summarize education, detail

                          education
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%            2              1
10%            2              1       Obs                 924
25%            2              1       Sum of Wgt.         924

50%            4                      Mean           4.363636
                        Largest       Std. Dev.      1.955579
75%            6             10
90%            7             10       Variance       3.824288
95%            7             10       Skewness       .0311431
99%            8             11       Kurtosis       1.995694

. 
. gen educationIQR = .
(930 missing values generated)

. replace educationIQR = 0 if education<=2
(275 real changes made)

. replace educationIQR = 1 if education>=6
(374 real changes made)

. replace educationIQR = . if education==.
(6 real changes made, 6 to missing)

. 
. 
. ***Code Binary Ethnicity Variables
. gen white = 0

. replace white = 1 if ethnicity==1
(678 real changes made)

. 
. gen black = 0

. replace black = 1 if ethnicity==2
(104 real changes made)

. 
. gen ethnicity_other = 0

. replace ethnicity_other = 1 if white==0 & black==0
(148 real changes made)

. 
. 
. ***Code Female Respondent Dummy
. gen female_respondent = 0

. replace female_respondent = 1 if gender==2
(474 real changes made)

. 
. 
. ***Code Income (1 = Least; 24 = Most; Drop Missing)
. gen income = hhi

. replace income = . if hhi==-3105
(50 real changes made, 50 to missing)

. 
. 
. ***Code Binary Hispanic Variable 
. gen hispanic_binary = 1

. replace hispanic_binary = 0 if hispanic==1 | hispanic==15  | hispanic==16 
(829 real changes made)

. 
. 
. ***Code Binary South Variable
. gen south = 0

. replace south = 1 if region==3
(343 real changes made)

. 
. 
. ***Code Treatment Variables 
. rename male male_name

. rename female female_name

. 
. gen female = 0

. replace female = 1 if cond9_dv!="" | cond10_dv!="" | cond13_dv!="" | cond14_dv!=""
(450 real changes made)

. 
. gen male = 0

. replace male = 1 if cond1_dv!="" | cond2_dv!="" | cond5_dv!="" | cond6_dv!="" 
(442 real changes made)

. 
. gen statusquo = 0

. replace statusquo = 1 if cond1_dv!="" | cond5_dv!="" | cond9_dv!="" | cond13_dv!="" 
(450 real changes made)

. 
. gen conciliatory = 0

. replace conciliatory = 1 if cond2_dv!="" | cond6_dv!="" | cond10_dv!="" | cond14_dv!="" 
(442 real changes made)

. 
. gen democrat = 0

. replace democrat = 1 if cond5_dv!="" | cond6_dv!="" | cond13_dv!="" | cond14_dv!="" 
(446 real changes made)

. 
. gen republican = 0

. replace republican = 1 if cond1_dv!="" | cond2_dv!="" | cond9_dv!="" | cond10_dv!="" 
(446 real changes made)

. 
. gen femsq = 0

. replace femsq = 1 if female==1 & statusquo==1
(228 real changes made)

. 
. gen malesq = 0

. replace malesq = 1 if male==1 & statusquo==1
(222 real changes made)

. 
. gen maleconc = 0

. replace maleconc= 1 if male==1 & conciliatory==1
(220 real changes made)

. 
. gen femconc = 0

. replace femconc= 1 if female==1 & conciliatory==1
(222 real changes made)

. 
. gen demsq = 0

. replace demsq = 1 if democrat==1 & statusquo==1
(226 real changes made)

. 
. gen repsq = 0

. replace repsq = 1 if republican==1 & statusquo==1
(224 real changes made)

. 
. gen demconc = 0

. replace demconc = 1 if democrat==1 & conciliatory==1
(220 real changes made)

. 
. gen repconc = 0

. replace repconc = 1 if republican==1 & conciliatory==1
(222 real changes made)

. 
. gen femsq_in = 0

. replace femsq_in = 1 if (femsq==1 & democratic_respondent==1 & democrat==1) | (femsq==1 & republican_respondent==1 
> & republican==1)
(90 real changes made)

. 
. gen femconc_in = 0

. replace femconc_in = 1 if (femconc==1 & democratic_respondent==1 & democrat==1) | (femconc==1 & republican_responde
> nt==1 & republican==1)
(86 real changes made)

. 
. gen malesq_in = 0

. replace malesq_in = 1 if (malesq==1 & democratic_respondent==1 & democrat==1) | (malesq==1 & republican_respondent=
> =1 & republican==1)
(87 real changes made)

. 
. gen maleconc_in = 0

. replace maleconc_in = 1 if (maleconc==1 & democratic_respondent==1 & democrat==1) | (maleconc==1 & republican_respo
> ndent==1 & republican==1)
(86 real changes made)

. 
. gen femsq_out = 0

. replace femsq_out = 1 if (femsq==1 & democratic_respondent==1 & republican==1) | (femsq==1 & republican_respondent=
> =1 & democrat==1)
(87 real changes made)

. 
. gen femconc_out = 0

. replace femconc_out = 1 if (femconc==1 & democratic_respondent==1 & republican==1) | (femconc==1 & republican_respo
> ndent==1 & democrat==1)
(87 real changes made)

. 
. gen malesq_out = 0

. replace malesq_out = 1 if (malesq==1 & democratic_respondent==1 & republican==1) | (malesq==1 & republican_responde
> nt==1 & democrat==1)
(87 real changes made)

. 
. gen maleconc_out = 0

. replace maleconc_out = 1 if (maleconc==1 & democratic_respondent==1 & republican==1) | (maleconc==1 & republican_re
> spondent==1 & democrat==1)
(84 real changes made)

. 
. gen in_partisan = 0

. replace in_partisan = 1 if (democratic_respondent==1 & democrat==1) | (republican_respondent==1 & republican==1)
(349 real changes made)

. 
. gen out_partisan = 0

. replace out_partisan = 1 if (democratic_respondent==1 & republican==1) | (republican_respondent==1 & democrat==1)
(345 real changes made)

. 
. 
. 
. ***Code Full Disapproval Variable 1 (1 = Strongly Approve; 7 = Strongly Disapprove)
. gen disapproval1 = .
(930 missing values generated)

. replace disapproval1 = 1 if cond1_dv=="Strongly approve" | cond2_dv=="Strongly approve" | cond5_dv=="Strongly appro
> ve" | cond6_dv=="Strongly approve" | cond9_dv=="Strongly approve" | cond10_dv=="Strongly approve" | cond13_dv=="Str
> ongly approve" | cond14_dv=="Strongly approve" 
(116 real changes made)

. replace disapproval1 = 2 if cond1_dv=="Approve" | cond2_dv=="Approve" | cond5_dv=="Approve" | cond6_dv=="Approve" |
>  cond9_dv=="Approve" | cond10_dv=="Approve" | cond13_dv=="Approve" | cond14_dv=="Approve" 
(195 real changes made)

. replace disapproval1 = 3 if cond1_dv=="Somewhat approve" | cond2_dv=="Somewhat approve" | cond5_dv=="Somewhat appro
> ve" | cond6_dv=="Somewhat approve" | cond9_dv=="Somewhat approve" | cond10_dv=="Somewhat approve" | cond13_dv=="Som
> ewhat approve" | cond14_dv=="Somewhat approve" 
(203 real changes made)

. replace disapproval1 = 4 if cond1_dv=="Neither approve nor disapprove" | cond2_dv=="Neither approve nor disapprove"
>  | cond5_dv=="Neither approve nor disapprove" | cond6_dv=="Neither approve nor disapprove" | cond9_dv=="Neither app
> rove nor disapprove" | cond10_dv=="Neither approve nor disapprove" | cond13_dv=="Neither approve nor disapprove" | 
> cond14_dv=="Neither approve nor disapprove" 
(170 real changes made)

. replace disapproval1 = 5 if cond1_dv=="Somewhat disapprove" | cond2_dv=="Somewhat disapprove" | cond5_dv=="Somewhat
>  disapprove" | cond6_dv=="Somewhat disapprove" | cond9_dv=="Somewhat disapprove" | cond10_dv=="Somewhat disapprove"
>  | cond13_dv=="Somewhat disapprove" | cond14_dv=="Somewhat disapprove" 
(106 real changes made)

. replace disapproval1 = 6 if cond1_dv=="Disapprove" | cond2_dv=="Disapproving" | cond5_dv=="Disapprove" | cond6_dv==
> "Disapprove" | cond9_dv=="Disapprove" | cond10_dv=="Disapprove" | cond13_dv=="Disapproving" | cond14_dv=="Disapprov
> e" 
(45 real changes made)

. replace disapproval1 = 7 if cond1_dv=="Strongly disapprove" | cond2_dv=="Strongly disapprove" | cond5_dv=="Strongly
>  disapprove" | cond6_dv=="Strongly disapprove" | cond9_dv=="Strongly disapprove" | cond10_dv=="Strongly disapprove"
>  | cond13_dv=="Strongly disapprove" | cond14_dv=="Strongly disapprove" 
(57 real changes made)

. 
. 
. ***Code Binart Disapproval Variable 1 (1 = Disapprove; 0 = Don't Disapprove)
. gen disapproval1_binary = 0

. replace disapproval1_binary = 1 if disapproval1>=5
(246 real changes made)

. replace disapproval1_binary = . if disapproval1==.
(38 real changes made, 38 to missing)

. 
. 
. ***Code Full Disapproval Variable 2 (1 = Strongly Approve; 7 = Strongly Disapprove)
. gen disapproval2 = .
(930 missing values generated)

. replace disapproval2 = 1 if cond1_outcome_dv=="Strongly approve" | cond2_outcome_dv=="Strongly approve" | cond5_out
> come_dv=="Strongly approve" | cond6_outcome_dv=="Strongly approve" | cond9_outcome_dv=="Strongly approve" | cond10_
> outcome_dv=="Strongly approve" | cond13_outcome_dv=="Strongly approve" | cond14_outcome_dv=="Strongly approve" 
(237 real changes made)

. replace disapproval2 = 2 if cond1_outcome_dv=="Approve" | cond2_outcome_dv=="Approve" | cond5_outcome_dv=="Approve"
>  | cond6_outcome_dv=="Approve" | cond9_outcome_dv=="Approve" | cond10_outcome_dv=="Approve" | cond13_outcome_dv=="A
> pprove" | cond14_outcome_dv=="Approve" 
(236 real changes made)

. replace disapproval2 = 3 if cond1_outcome_dv=="Somewhat approve" | cond2_outcome_dv=="Somewhat approve" | cond5_out
> come_dv=="Somewhat approve" | cond6_outcome_dv=="Somewhat approve" | cond9_outcome_dv=="Somewhat approve" | cond10_
> outcome_dv=="Somewhat approve" | cond13_outcome_dv=="Somewhat approve" | cond14_outcome_dv=="Somewhat approve" 
(155 real changes made)

. replace disapproval2 = 4 if cond1_outcome_dv=="Neither approve nor disapprove" | cond2_outcome_dv=="Neither approve
>  nor disapprove" | cond5_outcome_dv=="Neither approve nor disapprove" | cond6_outcome_dv=="Neither approve nor disa
> pprove" | cond9_outcome_dv=="Neither approve nor disapprove" | cond10_outcome_dv=="Neither approve nor disapprove" 
> | cond13_outcome_dv=="Neither approve nor disapprove" | cond14_outcome_dv=="Neither approve nor disapprove" 
(127 real changes made)

. replace disapproval2 = 5 if cond1_outcome_dv=="Somewhat disapprove" | cond2_outcome_dv=="Somewhat disapprove" | con
> d5_outcome_dv=="Somewhat disapprove" | cond6_outcome_dv=="Somewhat disapprove" | cond9_outcome_dv=="Somewhat disapp
> rove" | cond10_outcome_dv=="Somewhat disapprove" | cond13_outcome_dv=="Somewhat disapprove" | cond14_outcome_dv=="S
> omewhat disapprove" 
(40 real changes made)

. replace disapproval2 = 6 if cond1_outcome_dv=="Disapprove" | cond2_outcome_dv=="Disapprove" | cond5_outcome_dv=="Di
> sapprove" | cond6_outcome_dv=="Disapprove" | cond9_outcome_dv=="Disapprove" | cond10_outcome_dv=="Disapprove" | con
> d13_outcome_dv=="Disapprove" | cond14_outcome_dv=="Disapprove" 
(14 real changes made)

. replace disapproval2 = 7 if cond1_outcome_dv=="Strongly disapprove" | cond2_outcome_dv=="Strongly disapprove" | con
> d5_outcome_dv=="Strongly disapprove" | cond6_outcome_dv=="Strongly disapprove" | cond9_outcome_dv=="Strongly disapp
> rove" | cond10_outcome_dv=="Strongly disapprove" | cond13_outcome_dv=="Strongly disapprove" | cond14_outcome_dv=="S
> trongly disapprove" 
(22 real changes made)

. 
. 
. ***Code Binart Disapproval Variable 2 (1 = Disapprove; 0 = Don't Disapprove)
. gen disapproval2_binary = 0

. replace disapproval2_binary = 1 if disapproval2>=5
(175 real changes made)

. replace disapproval2_binary = . if disapproval2==.
(99 real changes made, 99 to missing)

. 
. 
. ***Code Mechanisms 
. 
. *Best Strategy
. gen beststrategy1 = .
(930 missing values generated)

. replace beststrategy1 = 7 if strategy1=="Strongly agree" 
(101 real changes made)

. replace beststrategy1 = 6 if strategy1=="Agree" 
(191 real changes made)

. replace beststrategy1 = 5 if strategy1=="Somewhat agree"
(169 real changes made)

. replace beststrategy1 = 4 if strategy1=="Neither agree nor disagree"
(163 real changes made)

. replace beststrategy1 = 3 if strategy1=="Somewhat disagree" 
(86 real changes made)

. replace beststrategy1 = 2 if strategy1=="Disagree" 
(57 real changes made)

. replace beststrategy1 = 1 if strategy1=="Strongly disagree" 
(65 real changes made)

. 
. gen beststrategy1_binary = 0

. replace beststrategy1_binary = 1 if beststrategy1>=5
(559 real changes made)

. replace beststrategy1_binary = . if beststrategy1==.
(98 real changes made, 98 to missing)

. 
. gen beststrategy2 = .
(930 missing values generated)

. replace beststrategy2 = 7 if strategy2=="Strongly agree" 
(194 real changes made)

. replace beststrategy2 = 6 if strategy2=="Agree" 
(219 real changes made)

. replace beststrategy2 = 5 if strategy2=="Somewhat agree"
(156 real changes made)

. replace beststrategy2 = 4 if strategy2=="Neither agree nor disagree"
(165 real changes made)

. replace beststrategy2 = 3 if strategy2=="Somewhat disagree" 
(53 real changes made)

. replace beststrategy2 = 2 if strategy2=="Disagree" 
(21 real changes made)

. replace beststrategy2 = 1 if strategy2=="Strongly disagree" 
(22 real changes made)

. 
. gen beststrategy2_binary = 0

. replace beststrategy2_binary = 1 if beststrategy2>=5
(669 real changes made)

. replace beststrategy2_binary = . if beststrategy2==.
(100 real changes made, 100 to missing)

. 
. *Pacifist 
. rename pacifist1 pacifist1_text

. rename pacifist2 pacifist2_text

. 
. gen pacifist1 = .
(930 missing values generated)

. replace pacifist1 = 7 if pacifist1_text=="Strongly agree" 
(76 real changes made)

. replace pacifist1 = 6 if pacifist1_text=="Agree" 
(83 real changes made)

. replace pacifist1 = 5 if pacifist1_text=="Somewhat agree"
(117 real changes made)

. replace pacifist1 = 4 if pacifist1_text=="Neither agree nor disagree"
(318 real changes made)

. replace pacifist1 = 3 if pacifist1_text=="Somewhat disagree" 
(99 real changes made)

. replace pacifist1 = 2 if pacifist1_text=="Disagree" 
(90 real changes made)

. replace pacifist1 = 1 if pacifist1_text=="Strongly disagree" 
(49 real changes made)

. 
. gen pacifist1_binary = 0

. replace pacifist1_binary = 1 if pacifist1>=5
(374 real changes made)

. replace pacifist1_binary = . if pacifist1==.
(98 real changes made, 98 to missing)

. 
. gen pacifist2 = .
(930 missing values generated)

. replace pacifist2 = 7 if pacifist2_text=="Strongly agree" 
(67 real changes made)

. replace pacifist2 = 6 if pacifist2_text=="Agree" 
(112 real changes made)

. replace pacifist2 = 5 if pacifist2_text=="Somewhat agree"
(98 real changes made)

. replace pacifist2 = 4 if pacifist2_text=="Neither agree nor disagree"
(317 real changes made)

. replace pacifist2 = 3 if pacifist2_text=="Somewhat disagree" 
(74 real changes made)

. replace pacifist2 = 2 if pacifist2_text=="Disagree" 
(98 real changes made)

. replace pacifist2 = 1 if pacifist2_text=="Strongly disagree" 
(64 real changes made)

. 
. gen pacifist2_binary = 0

. replace pacifist2_binary = 1 if pacifist2>=5
(377 real changes made)

. replace pacifist2_binary = . if pacifist2==.
(100 real changes made, 100 to missing)

. 
. *Warmonger 
. rename warmonger1 warmonger1_text

. rename warmonger2 warmonger2_text

. 
. gen warmonger1 = .
(930 missing values generated)

. replace warmonger1 = 7 if warmonger1_text=="Strongly agree" 
(31 real changes made)

. replace warmonger1 = 6 if warmonger1_text=="Agree" 
(34 real changes made)

. replace warmonger1 = 5 if warmonger1_text=="Somewhat agree"
(61 real changes made)

. replace warmonger1 = 4 if warmonger1_text=="Neither agree nor disagree"
(278 real changes made)

. replace warmonger1 = 3 if warmonger1_text=="Somewhat disagree" 
(127 real changes made)

. replace warmonger1 = 2 if warmonger1_text=="Disagree" 
(170 real changes made)

. replace warmonger1 = 1 if warmonger1_text=="Strongly disagree" 
(131 real changes made)

. 
. gen warmonger1_binary = 0

. replace warmonger1_binary = 1 if warmonger1>=5
(224 real changes made)

. replace warmonger1_binary = . if warmonger1==.
(98 real changes made, 98 to missing)

. 
. gen warmonger2 = .
(930 missing values generated)

. replace warmonger2 = 7 if warmonger2_text=="Strongly agree" 
(25 real changes made)

. replace warmonger2 = 6 if warmonger2_text=="Agree" 
(45 real changes made)

. replace warmonger2 = 5 if warmonger2_text=="Somewhat agree"
(52 real changes made)

. replace warmonger2 = 4 if warmonger2_text=="Neither agree nor disagree"
(287 real changes made)

. replace warmonger2 = 3 if warmonger2_text=="Somewhat disagree" 
(115 real changes made)

. replace warmonger2 = 2 if warmonger2_text=="Disagree" 
(166 real changes made)

. replace warmonger2 = 1 if warmonger2_text=="Strongly disagree" 
(140 real changes made)

. 
. gen warmonger2_binary = 0

. replace warmonger2_binary = 1 if warmonger2>=5
(222 real changes made)

. replace warmonger2_binary = . if warmonger2==.
(100 real changes made, 100 to missing)

. 
. *Moderate
. gen moderate = 0

. replace moderate = 1 if warmonger1<4 & pacifist1<4
(167 real changes made)

. replace moderate = . if warmonger1==. | pacifist1==.
(98 real changes made, 98 to missing)

. 
. *Competent 
. rename competent1 competent1_text

. 
. gen competent1 = .
(930 missing values generated)

. replace competent1 = 7 if competent1_text=="Strongly agree" 
(117 real changes made)

. replace competent1 = 6 if competent1_text=="Agree" 
(201 real changes made)

. replace competent1 = 5 if competent1_text=="Somewhat agree"
(175 real changes made)

. replace competent1 = 4 if competent1_text=="Neither agree nor disagree"
(205 real changes made)

. replace competent1 = 3 if competent1_text=="Somewhat disagree" 
(60 real changes made)

. replace competent1 = 2 if competent1_text=="Disagree" 
(35 real changes made)

. replace competent1 = 1 if competent1_text=="Strongly disagree" 
(39 real changes made)

. 
. gen competent1_binary = 0

. replace competent1_binary = 1 if competent1>=5
(591 real changes made)

. replace competent1_binary = . if competent1==.
(98 real changes made, 98 to missing)

. 
. *Tough 
. rename tough1 tough1_text

. 
. gen tough1 = .
(930 missing values generated)

. replace tough1 = 7 if tough1_text=="Strongly agree" 
(95 real changes made)

. replace tough1 = 6 if tough1_text=="Agree" 
(190 real changes made)

. replace tough1 = 5 if tough1_text=="Somewhat agree"
(162 real changes made)

. replace tough1 = 4 if tough1_text=="Neither agree nor disagree"
(202 real changes made)

. replace tough1 = 3 if tough1_text=="Somewhat disagree" 
(68 real changes made)

. replace tough1 = 2 if tough1_text=="Disagree" 
(62 real changes made)

. replace tough1 = 1 if tough1_text=="Strongly disagree" 
(53 real changes made)

. 
. gen tough1_binary = 0

. replace tough1_binary = 1 if tough1>=5
(545 real changes made)

. replace tough1_binary = . if tough1==.
(98 real changes made, 98 to missing)

. 
. *Trustworthy 
. rename trustworthy1 trustworthy1_text

. 
. gen trustworthy1 = .
(930 missing values generated)

. replace trustworthy1 = 7 if trustworthy1_text=="Strongly agree" 
(87 real changes made)

. replace trustworthy1 = 6 if trustworthy1_text=="Agree" 
(171 real changes made)

. replace trustworthy1 = 5 if trustworthy1_text=="Somewhat agree"
(137 real changes made)

. replace trustworthy1 = 4 if trustworthy1_text=="Neither agree nor disagree"
(310 real changes made)

. replace trustworthy1 = 3 if trustworthy1_text=="Somewhat disagree" 
(53 real changes made)

. replace trustworthy1 = 2 if trustworthy1_text=="Disagree" 
(35 real changes made)

. replace trustworthy1 = 1 if trustworthy1_text=="Strongly disagree" 
(39 real changes made)

. 
. gen trustworthy1_binary = 0

. replace trustworthy1_binary = 1 if trustworthy1>=5
(493 real changes made)

. replace trustworthy1_binary = . if trustworthy1==.
(98 real changes made, 98 to missing)

. 
. 
. ***Confounding Placebo (1 = Perceived President Non-White; 1 = White)
. gen nonwhite_placebo = 0

. replace nonwhite_placebo = 1 if race!="Caucasian/White"
(311 real changes made)

. replace nonwhite_placebo = . if race==""
(102 real changes made, 102 to missing)

. 
. 
. ***FP Orientation Placebo
. gen dove_placebo = .
(930 missing values generated)

. replace dove_placebo = 0 if hawkdove=="Usually favors military solutions over diplomatic ones"
(258 real changes made)

. replace dove_placebo = 0 if hawkdove=="Other"
(87 real changes made)

. replace dove_placebo = 1 if hawkdove=="Usually favors diplomatic solutions over military ones"
(483 real changes made)

. 
. 
. 
. ***Manipulation Checks (1 = Passed; 0 = Failed)
. 
. *Name Check
. gen name_manipcheck = 0

. replace name_manipcheck = 1 if male==1 & male_name=="Eric" & name=="Eric"
(148 real changes made)

. replace name_manipcheck = 1 if male==1 & male_name=="Steven" & name=="Steven"
(133 real changes made)

. replace name_manipcheck = 1 if female==1 & female_name=="Erica" & name=="Erica"
(151 real changes made)

. replace name_manipcheck = 1 if female==1 & female_name=="Stephanie" & name=="Stephanie"
(162 real changes made)

. 
. *Policy Check
. gen policy_manipcheck = 0

. replace policy_manipcheck = 1 if statusquo==1 & action=="Maintained the U.S. military  presence in the Arctic"
(324 real changes made)

. replace policy_manipcheck = 1 if conciliatory==1 & action=="Decreased the U.S. military presence in the Arctic"
(316 real changes made)

. 
. *Implied Gender Manip Check (i.e., got gender of leader right)
. gen implied_gender_manipcheck = 0

. replace implied_gender_manipcheck = 1 if (male==1) & (name=="Eric" | name=="Steven")
(301 real changes made)

. replace implied_gender_manipcheck = 1 if (female==1) & (name=="Erica" | name=="Stephanie")
(327 real changes made)

. 
. *Got All Manipulation Checks Correct
. gen all_manipcheck = 0

. replace all_manipcheck = 1 if name_manipcheck==1 & policy_manipcheck==1
(514 real changes made)

. 
end of do-file

. 
. ********************************************************************************
. *                                                FIGURE 2: STUDY 1 PREMIA                                          
>                 *
. ********************************************************************************
. 
. ***Main Effect of Gender -- Outcome 1, Binary DV
. reg disapproval1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        892
                                                F(4, 888)         =      79.28
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3286
                                                Root MSE          =     .39657

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .0745614   .0174357     4.28   0.000     .0403414    .1087814
     femconc |   .4234234   .0332365    12.74   0.000     .3581922    .4886547
      malesq |   .1036036   .0204992     5.05   0.000     .0633711    .1438361
    maleconc |   .3363636   .0319252    10.54   0.000     .2737059    .3990214
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq, level(95)

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .116102   .0533677     2.18   0.030     .0113605    .2208434
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq, level(90)

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .116102   .0533677     2.18   0.030     .0282283    .2039757
------------------------------------------------------------------------------

. 
. matrix study1_gender = J(1,5,.)

. matrix colnames study1_gender = premia ll95 ul95 ll90 ul90

. matrix rownames study1_gender = gender

. matrix study1_gender[1, 1] = .116102*100

. matrix study1_gender[1, 2] = .0113605*100

. matrix study1_gender[1, 3] = .2208434*100

. matrix study1_gender[1, 4] = .0282283*100

. matrix study1_gender[1, 5] = .2039757*100

. matrix list study1_gender

study1_gender[1,5]
          premia      ll95      ul95      ll90      ul90
gender   11.6102   1.13605  22.08434   2.82283  20.39757

. 
. *** Main Effect of Partisanship -- Outcome 1, Binary DV:
. reg disapproval1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =        892
                                                F(4, 888)         =      78.66
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3255
                                                Root MSE          =     .39747

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |    .079646   .0180502     4.41   0.000     .0442201     .115072
     demconc |   .4045455   .0331644    12.20   0.000     .3394556    .4696353
       repsq |   .0982143   .0199292     4.93   0.000     .0591004    .1373282
     repconc |   .3558559   .0322054    11.05   0.000     .2926484    .4190633
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq, level(95)

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0672579   .0534794     1.26   0.209    -.0377029    .1722187
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq, level(90)

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0672579   .0534794     1.26   0.209    -.0207998    .1553155
------------------------------------------------------------------------------

. 
. matrix study1_partisan = J(1,5,.)

. matrix colnames study1_partisan = premia ll95 ul95 ll90 ul90

. matrix rownames study1_partisan = partisan

. matrix study1_partisan[1, 1] = .0672579*100

. matrix study1_partisan[1, 2] = -.0377029*100

. matrix study1_partisan[1, 3] = .1722187*100

. matrix study1_partisan[1, 4] = -.0207998*100

. matrix study1_partisan[1, 5] = .1553155*100

. matrix list study1_partisan

study1_partisan[1,5]
            premia      ll95      ul95      ll90      ul90
partisan   6.72579  -3.77029  17.22187  -2.07998  15.53155

. 
. ***Create Figure 
. 
. coefplot (matrix(study1_gender[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel m
> labcolor(black) mlabposition(12) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study1_partisan[,1]), ci((2 3
> ) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcol
> or(black black) lwidth(.55 1.1))), legend(off) ylabel(1 `" "Gendered" "Peace Premium" "' 2  `" "Partisan" "Peace Pr
> emium" "', labsize(medium)) xlabel(-10(5)25, labsize(medium)) xmtick(-10(1)25) xtitle("Peace Premia (in % Points)",
>  size(medlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(%4.1f)

. graph export "${results}/figure2.eps", replace
(file ~/Desktop/ISQ Replication/results/figure2.eps written in EPS format)

. 
. eststo clear

. 
. ********************************************************************************
. *                                                FIGURE 3: STUDY 1 MECHANISMS                                      
>         *
. ********************************************************************************
. 
. *** Gender -- Best Strategy
. reg beststrategy1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     325.45
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6020
                                                Root MSE          =     .47076

------------------------------------------------------------------------------
             |               Robust
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .7175926   .0307041    23.37   0.000     .6573255    .7778597
     femconc |   .3444976   .0329499    10.46   0.000     .2798225    .4091727
      malesq |   .7038835   .0318856    22.08   0.000     .6412974    .7664696
    maleconc |   .4427861   .0351202    12.61   0.000     .3738511    .5117211
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1119976   .0654106     1.71   0.087    -.0163926    .2403878
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1119976   .0654106     1.71   0.087     .0042861     .219709
------------------------------------------------------------------------------

. 
. matrix study1_g_strategy = J(1,5,.)

. matrix colnames study1_g_strategy = premia ll95 ul95 ll90 ul90

. matrix rownames study1_g_strategy = gender

. matrix study1_g_strategy[1, 1] = .1119976*100

. matrix study1_g_strategy[1, 2] = -.0163926*100

. matrix study1_g_strategy[1, 3] = .2403878*100

. matrix study1_g_strategy[1, 4] = .0042861*100

. matrix study1_g_strategy[1, 5] = .219709*100

. matrix list study1_g_strategy

study1_g_strategy[1,5]
          premia      ll95      ul95      ll90      ul90
gender  11.19976  -1.63926  24.03878    .42861   21.9709

. 
. *** Party -- Best Strategy
. reg beststrategy1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     324.33
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5998
                                                Root MSE          =     .47203

------------------------------------------------------------------------------
             |               Robust
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .7177033   .0312104    23.00   0.000     .6564426    .7789641
     demconc |   .3913043   .0340031    11.51   0.000     .3245619    .4580468
       repsq |   .7042254   .0313468    22.47   0.000     .6426968    .7657539
     repconc |   .3940887   .0343795    11.46   0.000     .3266074      .46157
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0162623   .0655353     0.25   0.804    -.1123725    .1448971
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0162623   .0655353     0.25   0.804    -.0916543     .124179
------------------------------------------------------------------------------

. 
. matrix study1_p_strategy = J(1,5,.)

. matrix colnames study1_p_strategy = premia ll95 ul95 ll90 ul90

. matrix rownames study1_p_strategy = partisan

. matrix study1_p_strategy[1, 1] = .0162623*100

. matrix study1_p_strategy[1, 2] = -.1123725*100

. matrix study1_p_strategy[1, 3] = .1448971*100

. matrix study1_p_strategy[1, 4] = -.0916543*100

. matrix study1_p_strategy[1, 5] = .124179*100

. matrix list study1_p_strategy

study1_p_strategy[1,5]
             premia       ll95       ul95       ll90       ul90
partisan    1.62623  -11.23725   14.48971   -9.16543    12.4179

. 
. *** Gender -- Competent
. reg competent1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     360.64
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6221
                                                Root MSE          =     .47438

------------------------------------------------------------------------------
             |               Robust
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |        .75   .0295339    25.39   0.000       .69203      .80797
     femconc |   .4162679   .0341796    12.18   0.000     .3491791    .4833567
      malesq |   .6796117   .0325898    20.85   0.000     .6156433      .74358
    maleconc |   .5174129   .0353309    14.64   0.000     .4480642    .5867616
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1715333   .0659611     2.60   0.009     .0420628    .3010039
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1715333   .0659611     2.60   0.009     .0629155    .2801511
------------------------------------------------------------------------------

. 
. matrix study1_g_competent = J(1,5,.)

. matrix colnames study1_g_competent = premia ll95 ul95 ll90 ul90

. matrix rownames study1_g_competent = gender

. matrix study1_g_competent[1, 1] = .1715333*100

. matrix study1_g_competent[1, 2] = .0420628*100

. matrix study1_g_competent[1, 3] = .3010039*100

. matrix study1_g_competent[1, 4] = .0629155*100

. matrix study1_g_competent[1, 5] = .2801511*100

. matrix list study1_g_competent

study1_g_competent[1,5]
          premia      ll95      ul95      ll90      ul90
gender  17.15333   4.20628  30.10039   6.29155  28.01511

. 
. *** Party -- Competent
. reg competent1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     354.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6192
                                                Root MSE          =     .47615

------------------------------------------------------------------------------
             |               Robust
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .6985646   .0318181    21.95   0.000      .636111    .7610181
     demconc |   .4541063   .0346892    13.09   0.000     .3860172    .5221954
       repsq |   .7323944   .0304072    24.09   0.000     .6727101    .7920787
     repconc |   .4778325   .0351432    13.60   0.000     .4088523    .5468127
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0101035   .0661466    -0.15   0.879    -.1399383    .1197312
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0101035   .0661466    -0.15   0.879    -.1190269    .0988198
------------------------------------------------------------------------------

. 
. matrix study1_p_competent = J(1,5,.)

. matrix colnames study1_p_competent = premia ll95 ul95 ll90 ul90

. matrix rownames study1_p_competent = partisan

. matrix study1_p_competent[1, 1] = -.0101035*100

. matrix study1_p_competent[1, 2] = -.1399383*100

. matrix study1_p_competent[1, 3] = .1197312*100

. matrix study1_p_competent[1, 4] = -.1190269*100

. matrix study1_p_competent[1, 5] = .0988198*100

. matrix list study1_p_competent

study1_p_competent[1,5]
             premia       ll95       ul95       ll90       ul90
partisan   -1.01035  -13.99383   11.97312  -11.90269    9.88198

. 
. *** Gender -- Moderate
. reg moderate femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =      55.30
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2411
                                                Root MSE          =     .39123

------------------------------------------------------------------------------
             |               Robust
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .2962963   .0311442     9.51   0.000     .2351654    .3574272
     femconc |   .1004785   .0208457     4.82   0.000     .0595619     .141395
      malesq |   .2815534   .0314116     8.96   0.000     .2198976    .3432092
    maleconc |    .119403   .0229269     5.21   0.000     .0744014    .1644046
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0336674   .0540077     0.62   0.533    -.0723408    .1396756
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0336674   .0540077     0.62   0.533    -.0552669    .1226018
------------------------------------------------------------------------------

. 
. matrix study1_g_moderate = J(1,5,.)

. matrix colnames study1_g_moderate = premia ll95 ul95 ll90 ul90

. matrix rownames study1_g_moderate = gender

. matrix study1_g_moderate[1, 1] = .0336674*100

. matrix study1_g_moderate[1, 2] = -.0723408*100

. matrix study1_g_moderate[1, 3] = .1396756*100

. matrix study1_g_moderate[1, 4] = -.0552669*100

. matrix study1_g_moderate[1, 5] = .1226018*100

. matrix list study1_g_moderate

study1_g_moderate[1,5]
          premia      ll95      ul95      ll90      ul90
gender   3.36674  -7.23408  13.96756  -5.52669  12.26018

. 
. *** Party -- Moderate
. reg moderate demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =      55.28
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2408
                                                Root MSE          =     .39131

------------------------------------------------------------------------------
             |               Robust
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |    .291866   .0315227     9.26   0.000     .2299923    .3537397
     demconc |   .1111111    .021896     5.07   0.000      .068133    .1540892
       repsq |    .286385   .0310502     9.22   0.000     .2254387    .3473313
     repconc |   .1083744   .0218702     4.96   0.000     .0654468     .151302
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0027443   .0539956     0.05   0.959    -.1032401    .1087288
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0027443   .0539956     0.05   0.959    -.0861701    .0916587
------------------------------------------------------------------------------

. 
. matrix study1_p_moderate = J(1,5,.)

. matrix colnames study1_p_moderate = premia ll95 ul95 ll90 ul90

. matrix rownames study1_p_moderate = partisan

. matrix study1_p_moderate[1, 1] = .0027443*100

. matrix study1_p_moderate[1, 2] = -.1032401*100

. matrix study1_p_moderate[1, 3] = .1087288*100

. matrix study1_p_moderate[1, 4] = -.0861701*100

. matrix study1_p_moderate[1, 5] = .0916587*100

. matrix list study1_p_moderate

study1_p_moderate[1,5]
             premia       ll95       ul95       ll90       ul90
partisan     .27443  -10.32401   10.87288   -8.61701    9.16587

. 
. *** Gender -- Trustworthy
. reg trustworthy1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     202.96
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4974
                                                Root MSE          =     .48967

------------------------------------------------------------------------------
             |               Robust
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |    .587963   .0335709    17.51   0.000     .5220689     .653857
     femconc |    .354067   .0331596    10.68   0.000     .2889801    .4191538
      malesq |   .5631068   .0346414    16.26   0.000     .4951114    .6311022
    maleconc |   .3880597    .034455    11.26   0.000     .3204303    .4556891
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0588489   .0679245     0.87   0.387    -.0744756    .1921734
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0588489   .0679245     0.87   0.387    -.0530022    .1706999
------------------------------------------------------------------------------

. 
. matrix study1_g_trust = J(1,5,.)

. matrix colnames study1_g_trust = premia ll95 ul95 ll90 ul90

. matrix rownames study1_g_trust = gender

. matrix study1_g_trust[1, 1] = .0588489*100

. matrix study1_g_trust[1, 2] = -.0744756*100

. matrix study1_g_trust[1, 3] = .1921734*100

. matrix study1_g_trust[1, 4] = -.0530022*100

. matrix study1_g_trust[1, 5] = .1706999*100

. matrix list study1_g_trust

study1_g_trust[1,5]
          premia      ll95      ul95      ll90      ul90
gender   5.88489  -7.44756  19.21734  -5.30022  17.06999

. 
. *** Party -- Trustworthy
. reg trustworthy1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     204.10
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4984
                                                Root MSE          =     .48916

------------------------------------------------------------------------------
             |               Robust
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .5454545   .0345256    15.80   0.000     .4776865    .6132225
     demconc |   .3478261   .0331836    10.48   0.000     .2826921      .41296
       repsq |   .6056338   .0335669    18.04   0.000     .5397475    .6715201
     repconc |   .3940887   .0343795    11.46   0.000     .3266074      .46157
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0139167    .067837    -0.21   0.838    -.1470694    .1192361
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0139167    .067837    -0.21   0.838    -.1256236    .0977903
------------------------------------------------------------------------------

. 
. matrix study1_p_trust = J(1,5,.)

. matrix colnames study1_p_trust = premia ll95 ul95 ll90 ul90

. matrix rownames study1_p_trust = partisan

. matrix study1_p_trust[1, 1] = -.0139167*100

. matrix study1_p_trust[1, 2] = -.1470694*100

. matrix study1_p_trust[1, 3] = .1192361*100

. matrix study1_p_trust[1, 4] = -.1256236*100

. matrix study1_p_trust[1, 5] = .0977903*100

. matrix list study1_p_trust

study1_p_trust[1,5]
             premia       ll95       ul95       ll90       ul90
partisan   -1.39167  -14.70694   11.92361  -12.56236    9.77903

. 
. *** Gender -- Tough
. reg tough1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     345.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6146
                                                Root MSE          =     .45611

------------------------------------------------------------------------------
             |               Robust
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .7268519   .0303908    23.92   0.000     .6671998    .7865039
     femconc |   .3014354   .0318181     9.47   0.000     .2389819     .363889
      malesq |   .7475728   .0303394    24.64   0.000     .6880215    .8071241
    maleconc |   .3631841   .0340031    10.68   0.000     .2964416    .4299265
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0410277   .0633457     0.65   0.517    -.0833094    .1653648
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0410277   .0633457     0.65   0.517    -.0632835    .1453389
------------------------------------------------------------------------------

. 
. matrix study1_g_tough = J(1,5,.)

. matrix colnames study1_g_tough = premia ll95 ul95 ll90 ul90

. matrix rownames study1_g_tough = gender

. matrix study1_g_tough[1, 1] = .0410277*100

. matrix study1_g_tough[1, 2] = -.0833094*100

. matrix study1_g_tough[1, 3] = .1653648*100

. matrix study1_g_tough[1, 4] = -.0632835*100

. matrix study1_g_tough[1, 5] = .1453389*100

. matrix list study1_g_tough

study1_g_tough[1,5]
          premia      ll95      ul95      ll90      ul90
gender   4.10277  -8.33094  16.53648  -6.32835  14.53389

. 
. *** Party -- Tough
. reg tough1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =        832
                                                F(4, 828)         =     345.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6150
                                                Root MSE          =     .45588

------------------------------------------------------------------------------
             |               Robust
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .7464115   .0301667    24.74   0.000     .6871994    .8056236
     demconc |    .294686   .0317638     9.28   0.000      .232339     .357033
       repsq |   .7276995   .0305743    23.80   0.000     .6676872    .7877118
     repconc |   .3694581   .0339577    10.88   0.000     .3028049    .4361114
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0934841   .0632999     1.48   0.140    -.0307631    .2177313
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0934841   .0632999     1.48   0.140    -.0107516    .1977198
------------------------------------------------------------------------------

. 
. matrix study1_p_tough = J(1,5,.)

. matrix colnames study1_p_tough = premia ll95 ul95 ll90 ul90

. matrix rownames study1_p_tough = partisan

. matrix study1_p_tough[1, 1] = .0934841*100

. matrix study1_p_tough[1, 2] = -.0307631*100

. matrix study1_p_tough[1, 3] = .2177313*100

. matrix study1_p_tough[1, 4] = -.0107516*100

. matrix study1_p_tough[1, 5] = .1977198*100

. matrix list study1_p_tough

study1_p_tough[1,5]
            premia      ll95      ul95      ll90      ul90
partisan   9.34841  -3.07631  21.77313  -1.07516  19.77198

. 
. coefplot (matrix(study1_g_strategy[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlab
> el mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study1_g_competent[,1]), 
> ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciop
> ts(lcolor(black black) lwidth(.55 1.1))) (matrix(study1_g_moderate[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mf
> color(black) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (
> matrix(study1_g_trust[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabpositi
> on(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study1_g_tough[,1]), ci((2 3) (4 5)) m
> symbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcolor(black b
> lack) lwidth(.55 1.1))), legend(off) ylabel(.67 "Policy Credibility" .83  "Competence" 1  "Moderation" 1.17  "Trust
> worthiness" 1.33  "Toughness", labsize(medsmall)) xlabel(-20(5)35, labsize(medium)) xmtick(-20(1)35) xtitle("Gender
> ed Peace Premium" "(in % Points)", size(medlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(%4.1f)

. graph export "${results}/figure3a.eps", replace
(file ~/Desktop/ISQ Replication/results/figure3a.eps written in EPS format)

. 
. coefplot (matrix(study1_p_strategy[,1]), ci((2 3) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlab
> el mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study1_p_competent[,1]), 
> ci((2 3) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(11) mlabcolor(black) ciop
> ts(lcolor(black black) lwidth(.55 1.1))) (matrix(study1_p_moderate[,1]), ci((2 3) (4 5)) msymbol(S) msize(large) mf
> color(white) mlcolor(black) mlabel mlabposition(1) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (m
> atrix(study1_p_trust[,1]), ci((2 3) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabpositio
> n(11) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study1_p_tough[,1]), ci((2 3) (4 5)) ms
> ymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcolor(black bl
> ack) lwidth(.55 1.1))), legend(off) ylabel(.67 "Policy Credibility" .83  "Competence" 1  "Moderation" 1.17  "Trustw
> orthiness" 1.33  "Toughness", labsize(medsmall)) xlabel(-20(5)35, labsize(medium)) xmtick(-20(1)35) xtitle("Partisa
> n Peace Premium" "(in % Points)", size(medlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(%4.1f)

. graph export "${results}/figure3b.eps", replace
(file ~/Desktop/ISQ Replication/results/figure3b.eps written in EPS format)

. 
. eststo clear

. 
. ********************************************************************************
. *                                                        TABLE 1: STUDY 1 SUCCESS                                  
>                 *
. ********************************************************************************
. 
. *Binary DV
. reg disapproval2_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        831
                                                F(4, 827)         =      21.12
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1037
                                                Root MSE          =     .28701

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .0601852   .0162213     3.71   0.000     .0283453     .092025
     femconc |   .1339713   .0236182     5.67   0.000     .0876126    .1803299
      malesq |   .0582524   .0163583     3.56   0.000     .0261437    .0903611
    maleconc |       .115   .0226127     5.09   0.000     .0706149    .1593851
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0170385   .0399985     0.43   0.670     -.061472    .0955491
------------------------------------------------------------------------------

. 
. *Full DV
. reg disapproval2 femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        831
                                                F(4, 827)         =     648.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7573
                                                Root MSE          =     1.4527

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   2.273148   .0893744    25.43   0.000     2.097721    2.448576
     femconc |   2.784689   .1142384    24.38   0.000     2.560458     3.00892
      malesq |   2.441748   .0934494    26.13   0.000     2.258322    2.625173
    maleconc |       2.72   .1049333    25.92   0.000     2.514033    2.925967
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq    

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2332884   .2019455     1.16   0.248    -.1630976    .6296745
------------------------------------------------------------------------------

.         
. *Passed Manipulation Check / Binary DV
. reg disapproval2_binary femsq femconc malesq maleconc if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =        514
                                                F(4, 510)         =      12.91
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1144
                                                Root MSE          =     .28262

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .0437956    .017552     2.50   0.013     .0093125    .0782788
     femconc |    .141844   .0294968     4.81   0.000     .0838937    .1997942
      malesq |   .0413223   .0181649     2.27   0.023     .0056351    .0770095
    maleconc |   .1304348   .0315279     4.14   0.000     .0684942    .1923754
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0089359   .0500211     0.18   0.858    -.0893369    .1072086
------------------------------------------------------------------------------

. 
. *Passed Manipulation Check / Full DV
. reg disapproval2 femsq femconc malesq maleconc if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =        514
                                                F(4, 510)         =     363.28
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7326
                                                Root MSE          =     1.4311

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   1.963504   .0957728    20.50   0.000     1.775346    2.151661
     femconc |    2.64539   .1431571    18.48   0.000      2.36414     2.92664
      malesq |   2.198347    .111078    19.79   0.000      1.98012    2.416574
    maleconc |   2.573913   .1486924    17.31   0.000     2.281788    2.866038
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq    

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3063205   .2532077     1.21   0.227     -.191138     .803779
------------------------------------------------------------------------------

. 
. ********************************************************************************
. *                                        TABLE A-1: STUDY 1 7-POINT SCALE                                          
>         *
. ********************************************************************************
. 
. ***Main Effect of Gender -- Outcome 1, Full DV
. reg disapproval1 femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =        892
                                                F(4, 888)         =    1089.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8360
                                                Root MSE          =     1.5198

------------------------------------------------------------------------------
             |               Robust
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   2.622807   .0851886    30.79   0.000     2.455613    2.790002
     femconc |   4.211712   .1143059    36.85   0.000      3.98737    4.436053
      malesq |   2.788288   .0941656    29.61   0.000     2.603475    2.973101
    maleconc |   3.827273   .1115385    34.31   0.000     3.608363    4.046183
------------------------------------------------------------------------------

. lincom femconc-femsq

 ( 1)  - femsq + femconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.588905   .1425586    11.15   0.000     1.309114    1.868696
------------------------------------------------------------------------------

. lincom maleconc-malesq

 ( 1)  - malesq + maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.038984   .1459726     7.12   0.000     .7524929    1.325476
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5499203   .2040366     2.70   0.007       .14947    .9503705
------------------------------------------------------------------------------

. 
. *** Main Effect of Partisanship -- Outcome 1, Full DV
. reg disapproval1 demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =        892
                                                F(4, 888)         =    1084.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8348
                                                Root MSE          =     1.5255

------------------------------------------------------------------------------
             |               Robust
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   2.650442   .0863789    30.68   0.000     2.480912    2.819973
     demconc |        4.1   .1187801    34.52   0.000     3.866877    4.333123
       repsq |   2.758929   .0931028    29.63   0.000     2.576201    2.941656
     repconc |   3.941441   .1081855    36.43   0.000     3.729112    4.153771
------------------------------------------------------------------------------

. lincom demconc-demsq

 ( 1)  - demsq + demconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.449558   .1468674     9.87   0.000      1.16131    1.737805
------------------------------------------------------------------------------

. lincom repconc-repsq

 ( 1)  - repsq + repconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.182513   .1427314     8.28   0.000     .9023827    1.462643
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2670447   .2047981     1.30   0.193    -.1349002    .6689895
------------------------------------------------------------------------------

. 
. ********************************************************************************
. *                                        TABLE A-2: STUDY 1 MANIPULATION CHECK                                     
> *
. ********************************************************************************
. 
. ***Main Effect of Gender -- Outcome 1, Binary DV
. reg disapproval1_binary femsq femconc malesq maleconc if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =        514
                                                F(4, 510)         =      60.23
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4085
                                                Root MSE          =     .39861

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .0656934   .0212492     3.09   0.002     .0239468    .1074401
     femconc |   .5106383   .0422628    12.08   0.000     .4276076     .593669
      malesq |   .0909091   .0262368     3.46   0.001     .0393636    .1424546
    maleconc |   .3913043   .0456883     8.56   0.000     .3015439    .4810648
------------------------------------------------------------------------------

. lincom femconc-femsq

 ( 1)  - femsq + femconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4449449   .0473041     9.41   0.000     .3520101    .5378797
------------------------------------------------------------------------------

. lincom maleconc-malesq

 ( 1)  - malesq + maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3003953   .0526858     5.70   0.000     .1968874    .4039031
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1445496   .0708058     2.04   0.042     .0054426    .2836566
------------------------------------------------------------------------------

. 
. *** Main Effect of Partisanship -- Outcome 1, Binary DV
. reg disapproval1_binary demsq demconc repsq repconc if policy_manipcheck==1, robust noconst

Linear regression                               Number of obs     =        640
                                                F(4, 636)         =      70.50
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3855
                                                Root MSE          =     .40291

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |    .081761   .0217979     3.75   0.000     .0389565    .1245655
     demconc |   .4727273    .038989    12.12   0.000     .3961645    .5492901
       repsq |   .0909091   .0224505     4.05   0.000     .0468229    .1349952
     repconc |    .410596   .0401594    10.22   0.000      .331735     .489457
------------------------------------------------------------------------------

. lincom demconc-demsq

 ( 1)  - demsq + demconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3909663   .0446687     8.75   0.000     .3032503    .4786822
------------------------------------------------------------------------------

. lincom repconc-repsq

 ( 1)  - repsq + repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3196869   .0460087     6.95   0.000     .2293396    .4100343
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0712793   .0641256     1.11   0.267    -.0546442    .1972028
------------------------------------------------------------------------------

. 
. ********************************************************************************
. *                                                TABLE A-3: STUDY 1 WITH COVARIATES                                
>         *
. ********************************************************************************
. 
. eststo clear

. 
. *Model 1: Main Effect of Gender -- Outcome 1, Binary DV
. eststo: reg disapproval1_binary femsq femconc malesq maleconc democrat hostsexism benevsexism secordersexism hawkis
> h female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        813
                                                F(17, 796)        =      22.89
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3878
                                                Root MSE          =     .38427

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  femsq |  -.4399007   .1047898    -4.20   0.000    -.6455977   -.2342037
                femconc |    -.07135   .1046485    -0.68   0.496    -.2767697    .1340698
                 malesq |  -.4040574   .1074661    -3.76   0.000    -.6150078    -.193107
               maleconc |  -.1745182   .1051467    -1.66   0.097    -.3809157    .0318794
               democrat |   .0159419   .0270871     0.59   0.556    -.0372286    .0691124
             hostsexism |   .0358351   .0161339     2.22   0.027     .0041651    .0675051
            benevsexism |  -.0239424   .0132245    -1.81   0.071    -.0499014    .0020166
         secordersexism |   .0429664   .0139688     3.08   0.002     .0155464    .0703863
                hawkish |   .0450614   .0179876     2.51   0.012     .0097526    .0803702
      female_respondent |   .0017172   .0275753     0.06   0.950    -.0524117    .0558461
political_identfication |   .0233448   .0076407     3.06   0.002     .0083466     .038343
              education |   .0058642   .0067815     0.86   0.387    -.0074476    .0191759
                    hhi |  -6.92e-06   .0000215    -0.32   0.748    -.0000491    .0000353
                    age |   .0009923   .0008311     1.19   0.233    -.0006392    .0026237
                  white |   .0314652   .0334501     0.94   0.347    -.0341956    .0971259
            SexismOrder |  -.0232913   .0272545    -0.85   0.393    -.0767905    .0302079
       nonwhite_placebo |  -.0310309   .0322344    -0.96   0.336    -.0943054    .0322437
-----------------------------------------------------------------------------------------
(est1 stored)

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1390115   .0543388     2.56   0.011     .0323473    .2456757
------------------------------------------------------------------------------

.         
. *Model 2: Main Effect of Gender -- Outcome 1, Full DV
. eststo: reg disapproval1 femsq femconc malesq maleconc democrat hostsexism benevsexism secordersexism hawkish femal
> e_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        813
                                                F(17, 796)        =     244.87
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8403
                                                Root MSE          =     1.4999

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  femsq |   1.566511   .4240889     3.69   0.000     .7340461    2.398976
                femconc |   3.174214   .4211424     7.54   0.000     2.347533    4.000895
                 malesq |   1.752788   .4301237     4.08   0.000     .9084772    2.597099
               maleconc |   2.781681   .4209457     6.61   0.000     1.955386    3.607976
               democrat |   .0006271    .106231     0.01   0.995     -.207899    .2091532
             hostsexism |   .1163609   .0664381     1.75   0.080    -.0140538    .2467756
            benevsexism |  -.0753721   .0566473    -1.33   0.184    -.1865678    .0358237
         secordersexism |   .1022204   .0574152     1.78   0.075    -.0104827    .2149234
                hawkish |   .0570307   .0729981     0.78   0.435    -.0862608    .2003221
      female_respondent |   .0384051   .1079443     0.36   0.722    -.1734841    .2502942
political_identfication |   .0954347   .0309661     3.08   0.002     .0346499    .1562194
              education |  -.0316236   .0271775    -1.16   0.245    -.0849715    .0217244
                    hhi |   .0000635    .000081     0.78   0.433    -.0000955    .0002225
                    age |    .002172   .0032178     0.67   0.500    -.0041444    .0084884
                  white |   .0490254   .1275461     0.38   0.701     -.201341    .2993918
            SexismOrder |  -.0567047   .1072309    -0.53   0.597    -.2671934     .153784
       nonwhite_placebo |   .0049928   .1317433     0.04   0.970    -.2536126    .2635981
-----------------------------------------------------------------------------------------
(est2 stored)

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5788097   .2108249     2.75   0.006     .1649712    .9926482
------------------------------------------------------------------------------

. 
. *Model 3: Main Effect of Partisanship -- Outcome 1, Binary DV
. eststo: reg disapproval1_binary demsq demconc repsq repconc female hostsexism benevsexism secordersexism hawkish fe
> male_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        813
                                                F(17, 796)        =      22.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3836
                                                Root MSE          =     .38558

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  demsq |  -.4321343    .107328    -4.03   0.000    -.6428136    -.221455
                demconc |  -.1026502   .1060189    -0.97   0.333    -.3107597    .1054594
                  repsq |  -.4179752   .1080619    -3.87   0.000    -.6300951   -.2058553
                repconc |  -.1472859   .1058227    -1.39   0.164    -.3550103    .0604386
                 female |   .0322366   .0276281     1.17   0.244     -.021996    .0864692
             hostsexism |   .0350121   .0161609     2.17   0.031     .0032891     .066735
            benevsexism |  -.0233167   .0132556    -1.76   0.079    -.0493368    .0027034
         secordersexism |   .0410571   .0139309     2.95   0.003     .0137114    .0684028
                hawkish |    .043848   .0180827     2.42   0.016     .0083526    .0793433
      female_respondent |   .0006206   .0276672     0.02   0.982    -.0536886    .0549298
political_identfication |   .0233138   .0076455     3.05   0.002     .0083061    .0383216
              education |   .0070701   .0067853     1.04   0.298     -.006249    .0203892
                    hhi |  -6.30e-06   .0000216    -0.29   0.770    -.0000486     .000036
                    age |    .001055   .0008311     1.27   0.205    -.0005764    .0026863
                  white |   .0302342   .0333904     0.91   0.365    -.0353094    .0957779
            SexismOrder |  -.0252635   .0273484    -0.92   0.356     -.078947      .02842
       nonwhite_placebo |  -.0294255   .0323516    -0.91   0.363    -.0929299     .034079
-----------------------------------------------------------------------------------------
(est3 stored)

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0587948   .0545436     1.08   0.281    -.0482715    .1658612
------------------------------------------------------------------------------

.         
. *Model 4: Main Effect of Partisanship -- Outcome 1, Full DV
. eststo: reg disapproval1 demsq demconc repsq repconc female hostsexism benevsexism secordersexism hawkish female_re
> spondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        813
                                                F(17, 796)        =     243.86
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8391
                                                Root MSE          =     1.5058

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  demsq |   1.570796   .4320853     3.64   0.000     .7226348    2.418957
                demconc |   3.014658     .42821     7.04   0.000     2.174104    3.855212
                  repsq |   1.694335    .430972     3.93   0.000     .8483588    2.540311
                repconc |   2.895774   .4217141     6.87   0.000     2.067971    3.723577
                 female |   .0971808   .1086123     0.89   0.371    -.1160195    .3103811
             hostsexism |   .1129382    .066446     1.70   0.090    -.0174919    .2433683
            benevsexism |  -.0727756   .0566882    -1.28   0.200    -.1840516    .0385003
         secordersexism |   .0942955   .0577537     1.63   0.103    -.0190721    .2076631
                hawkish |   .0519792   .0733643     0.71   0.479    -.0920312    .1959896
      female_respondent |   .0338514   .1083205     0.31   0.755    -.1787763    .2464791
political_identfication |   .0952965   .0310568     3.07   0.002     .0343336    .1562593
              education |  -.0266196   .0271592    -0.98   0.327    -.0799316    .0266925
                    hhi |   .0000661   .0000816     0.81   0.418    -.0000941    .0002263
                    age |   .0024318    .003216     0.76   0.450     -.003881    .0087446
                  white |     .04392   .1273553     0.34   0.730     -.206072    .2939119
            SexismOrder |  -.0649016   .1075386    -0.60   0.546    -.2759943    .1461911
       nonwhite_placebo |   .0116209    .132451     0.09   0.930    -.2483737    .2716155
-----------------------------------------------------------------------------------------
(est4 stored)

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2424225   .2130944     1.14   0.256    -.1758709     .660716
------------------------------------------------------------------------------

. 
. esttab using "${results}/table_a3.tex", cells(b(fmt(3)) ci(fmt(3) par)) noeqlines eqlabels(none) nogaps se varlabel
> s(demsq "Democratic x Status Quo" demconc "Democratic x Conciliatory" repsq "Republican x Status Quo" repconc "Repu
> blican x Conciliatory" femsq "Female x Status Quo" femconc "Female x Conciliatory" malesq "Male x Status Quo" malec
> onc "Male x Conciliatory" democrat "Democratic President" female "Female President") keep(malesq maleconc femsq fem
> conc repsq repconc demsq demconc female democrat) order(malesq maleconc femsq femconc repsq repconc demsq demconc f
> emale democrat) label star(* 0.10 ** 0.05 *** .01) nonotes mtitle("Disapproval (Binary)" "Disapproval (7-Point)" "D
> isapproval (Binary)" "Disapproval (7-Point)") b(3) se(3) replace
(output written to ~/Desktop/ISQ Replication/results/table_a3.tex)

. 
. eststo clear

. 
. ********************************************************************************
. *                                TABLE A-4: STUDY 1 MEDIATION CREDIBILITY                                          
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Male
. medeff (regress beststrategy1 conciliatory democrat hostsexism benevsexism secordersexism hawkish female_respondent
>  political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 beststrategy1 
> conciliatory democrat hostsexism benevsexism hawkish female_respondent political_identfication education hhi age wh
> ite SexismOrder nonwhite_placebo) if male==1, mediate(beststrategy1) treat(conciliatory) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       397
-------------+----------------------------------   F(14, 382)      =      5.99
       Model |  204.572066        14  14.6122904   Prob > F        =    0.0000
    Residual |  931.503501       382  2.43849084   R-squared       =    0.1801
-------------+----------------------------------   Adj R-squared   =    0.1500
       Total |  1136.07557       396  2.86887769   Root MSE        =    1.5616

-----------------------------------------------------------------------------------------
          beststrategy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -1.083252   .1578511    -6.86   0.000    -1.393618   -.7728862
               democrat |  -.1739902   .1580565    -1.10   0.272    -.4847599    .1367794
             hostsexism |  -.0169546   .0908014    -0.19   0.852    -.1954876    .1615785
            benevsexism |   .2359652   .0735827     3.21   0.001     .0912873     .380643
         secordersexism |    -.16051   .0803604    -2.00   0.046    -.3185141    -.002506
                hawkish |   .0333687    .096297     0.35   0.729    -.1559697    .2227071
      female_respondent |    -.02837   .1626533    -0.17   0.862    -.3481779    .2914378
political_identfication |  -.1365115   .0451929    -3.02   0.003    -.2253695   -.0476535
              education |   .0507714   .0410915     1.24   0.217    -.0300225    .1315653
                    hhi |  -.0000961   .0001254    -0.77   0.444    -.0003425    .0001504
                    age |  -.0054923   .0048011    -1.14   0.253    -.0149321    .0039475
                  white |   .0512059   .1994167     0.26   0.797    -.3408859    .4432978
            SexismOrder |   .2755431   .1586203     1.74   0.083    -.0363351    .5874213
       nonwhite_placebo |  -.0603334   .2078773    -0.29   0.772    -.4690603    .3483935
                  _cons |   5.360606   .5910417     9.07   0.000     4.198504    6.522709
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       397
-------------+----------------------------------   F(14, 382)      =     74.36
       Model |    779.8298        14  55.7021286   Prob > F        =    0.0000
    Residual |  286.134936       382  .749044334   R-squared       =    0.7316
-------------+----------------------------------   Adj R-squared   =    0.7217
       Total |  1065.96474       396  2.69183014   Root MSE        =    .86547

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .1706388    .092722     1.84   0.066    -.0116707    .3529483
          beststrategy1 |  -.7955094   .0282102   -28.20   0.000     -.850976   -.7400427
               democrat |  -.0568464   .0876288    -0.65   0.517    -.2291417    .1154488
             hostsexism |  -.0181044   .0498914    -0.36   0.717    -.1162005    .0799918
            benevsexism |   .0564876   .0396359     1.43   0.155    -.0214442    .1344194
                hawkish |   .0184722   .0533787     0.35   0.729    -.0864806    .1234251
      female_respondent |  -.0360988   .0900525    -0.40   0.689    -.2131593    .1409618
political_identfication |    .049774   .0253231     1.97   0.050    -.0000161    .0995641
              education |  -.0085726   .0228193    -0.38   0.707    -.0534398    .0362945
                    hhi |   .0000214   .0000688     0.31   0.756    -.0001139    .0001567
                    age |   .0009686   .0026596     0.36   0.716    -.0042607    .0061978
                  white |   .0011608   .1105286     0.01   0.992    -.2161597    .2184814
            SexismOrder |  -.1763897   .0881219    -2.00   0.046    -.3496544    -.003125
       nonwhite_placebo |  -.1103126   .1152153    -0.96   0.339    -.3368482    .1162231
                  _cons |   6.624236   .3220446    20.57   0.000     5.991034    7.257438
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .8581036      .5893385      1.137594
        Direct Effect          |  .1745074     -.0052477      .3587946
        Total Effect           |  1.032611      .9351658      1.138908
        % of Tot Eff mediated  |  .8318326       .753444      .9175952
------------------------------------------------------------------------------------

. 
. ***Female       
. medeff (regress beststrategy1 conciliatory democrat hostsexism benevsexism secordersexism hawkish female_respondent
>  political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 beststrategy1 
> conciliatory democrat hostsexism benevsexism hawkish female_respondent political_identfication education hhi age wh
> ite SexismOrder nonwhite_placebo) if female==1, mediate(beststrategy1) treat(conciliatory) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       416
-------------+----------------------------------   F(14, 401)      =     10.63
       Model |  351.234283        14  25.0881631   Prob > F        =    0.0000
    Residual |  946.294563       401  2.35983682   R-squared       =    0.2707
-------------+----------------------------------   Adj R-squared   =    0.2452
       Total |  1297.52885       415  3.12657553   Root MSE        =    1.5362

-----------------------------------------------------------------------------------------
          beststrategy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -1.639492   .1524223   -10.76   0.000    -1.939138   -1.339845
               democrat |   -.069726   .1517043    -0.46   0.646    -.3679611    .2285091
             hostsexism |  -.2499812   .0864462    -2.89   0.004    -.4199256   -.0800369
            benevsexism |   .0112139   .0712302     0.16   0.875    -.1288173    .1512452
         secordersexism |  -.0878364   .0746187    -1.18   0.240    -.2345291    .0588564
                hawkish |   .0276628   .0935517     0.30   0.768    -.1562502    .2115759
      female_respondent |  -.1955569   .1595372    -1.23   0.221    -.5091906    .1180769
political_identfication |  -.0555138   .0419092    -1.32   0.186     -.137903    .0268753
              education |  -.0177736   .0403488    -0.44   0.660    -.0970953    .0615481
                    hhi |  -.0000898   .0001097    -0.82   0.414    -.0003054    .0001259
                    age |  -.0004117   .0047791    -0.09   0.931     -.009807    .0089835
                  white |  -.3782089   .1858028    -2.04   0.042    -.7434782   -.0129396
            SexismOrder |  -.2979687    .153929    -1.94   0.054    -.6005773      .00464
       nonwhite_placebo |  -.3816759    .172014    -2.22   0.027    -.7198378   -.0435141
                  _cons |   7.255826   .5883524    12.33   0.000     6.099186    8.412467
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       416
-------------+----------------------------------   F(14, 401)      =     97.44
       Model |  911.859569        14  65.1328263   Prob > F        =    0.0000
    Residual |  268.053893       401  .668463573   R-squared       =    0.7728
-------------+----------------------------------   Adj R-squared   =    0.7649
       Total |  1179.91346       415  2.84316497   Root MSE        =     .8176

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .3063067   .0918176     3.34   0.001     .1258028    .4868107
          beststrategy1 |  -.7997088   .0265324   -30.14   0.000    -.8518688   -.7475488
               democrat |  -.1244561   .0807479    -1.54   0.124    -.2831982    .0342859
             hostsexism |    .032925   .0454163     0.72   0.469    -.0563588    .1222088
            benevsexism |  -.0139281   .0365675    -0.38   0.703     -.085816    .0579597
                hawkish |   .1290623   .0497734     2.59   0.010     .0312129    .2269118
      female_respondent |   .0018685   .0850682     0.02   0.982    -.1653669    .1691039
political_identfication |  -.0031066   .0223531    -0.14   0.890    -.0470505    .0408373
              education |  -.0228475   .0214358    -1.07   0.287     -.064988     .019293
                    hhi |  -.0000206   .0000584    -0.35   0.725    -.0001354    .0000943
                    age |  -.0006916   .0025426    -0.27   0.786    -.0056902    .0043069
                  white |  -.1511767   .0992425    -1.52   0.128    -.3462772    .0439238
            SexismOrder |    .011174   .0820726     0.14   0.892    -.1501723    .1725202
       nonwhite_placebo |  -.2747422   .0920782    -2.98   0.003    -.4557586   -.0937259
                  _cons |   6.760145   .3357661    20.13   0.000     6.100063    7.420227
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  1.307832      1.022165      1.608154
        Direct Effect          |  .3101376      .1321358      .4926271
        Total Effect           |  1.617969      1.495341      1.746624
        % of Tot Eff mediated  |  .8085584      .7487769      .8746041
------------------------------------------------------------------------------------

. 
. 
. ********************************************************************************
. *                                TABLE A-5: STUDY 1 MEDIATION COMPETENCE                                           
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Male
. medeff (regress competent1 conciliatory democrat hostsexism benevsexism secordersexism hawkish female_respondent po
> litical_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 competent1 concil
> iatory democrat hostsexism benevsexism hawkish female_respondent political_identfication education hhi age white Se
> xismOrder nonwhite_placebo) if male==1, mediate(competent1) treat(conciliatory) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       397
-------------+----------------------------------   F(14, 382)      =      4.67
       Model |  132.157157        14  9.43979696   Prob > F        =    0.0000
    Residual |  771.535538       382  2.01972654   R-squared       =    0.1462
-------------+----------------------------------   Adj R-squared   =    0.1150
       Total |  903.692695       396  2.28205226   Root MSE        =    1.4212

-----------------------------------------------------------------------------------------
             competent1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -.7813654   .1436592    -5.44   0.000    -1.063827   -.4989036
               democrat |  -.1487482   .1438461    -1.03   0.302    -.4315775     .134081
             hostsexism |   -.099203   .0826377    -1.20   0.231    -.2616847    .0632786
            benevsexism |   .2094789   .0669671     3.13   0.002     .0778086    .3411492
         secordersexism |  -.0976238   .0731354    -1.33   0.183    -.2414222    .0461745
                hawkish |  -.0297835   .0876392    -0.34   0.734     -.202099    .1425321
      female_respondent |  -.0228425   .1480296    -0.15   0.877    -.3138974    .2682124
political_identfication |  -.1053744   .0411298    -2.56   0.011    -.1862434   -.0245053
              education |   .0129924   .0373971     0.35   0.728    -.0605376    .0865224
                    hhi |   .0000218   .0001141     0.19   0.848    -.0002025    .0002462
                    age |  -.0030114   .0043694    -0.69   0.491    -.0116025    .0055797
                  white |   .0173227   .1814877     0.10   0.924    -.3395173    .3741627
            SexismOrder |   .0658035   .1443592     0.46   0.649    -.2180346    .3496417
       nonwhite_placebo |  -.1536798   .1891876    -0.81   0.417    -.5256593    .2182996
                  _cons |   5.840642   .5379029    10.86   0.000     4.783021    6.898264
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       397
-------------+----------------------------------   F(14, 382)      =     28.27
       Model |   542.39411        14  38.7424364   Prob > F        =    0.0000
    Residual |  523.570626       382  1.37060373   R-squared       =    0.5088
-------------+----------------------------------   Adj R-squared   =    0.4908
       Total |  1065.96474       396  2.69183014   Root MSE        =    1.1707

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .5051096   .1228299     4.11   0.000     .2636023    .7466169
             competent1 |  -.6797978   .0420501   -16.17   0.000    -.7624765   -.5971191
               democrat |  -.0249471   .1185252    -0.21   0.833    -.2579907    .2080964
             hostsexism |   -.081137   .0675817    -1.20   0.231    -.2140158    .0517417
            benevsexism |   .0264332   .0536592     0.49   0.623    -.0790711    .1319376
                hawkish |  -.0288433   .0722036    -0.40   0.690    -.1708095    .1131229
      female_respondent |  -.0230955   .1218102    -0.19   0.850    -.2625979    .2164069
political_identfication |   .0858294   .0341508     2.51   0.012     .0186824    .1529765
              education |  -.0401257   .0308117    -1.30   0.194    -.1007075    .0204561
                    hhi |   .0000993   .0000931     1.07   0.287    -.0000837    .0002823
                    age |   .0035579   .0035927     0.99   0.323    -.0035061    .0106219
                  white |  -.0293863   .1494996    -0.20   0.844    -.3233314    .2645589
            SexismOrder |   -.345139   .1188111    -2.90   0.004    -.5787447   -.1115334
       nonwhite_placebo |  -.1686504   .1559665    -1.08   0.280    -.4753107    .1380099
                  _cons |   6.535043    .457878    14.27   0.000     5.634766    7.435319
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .5289438      .3166937      .7584051
        Direct Effect          |  .5102343      .2721108      .7543615
        Total Effect           |  1.039178      .9640467      1.105529
        % of Tot Eff mediated  |   .507867      .4784529      .5486703
------------------------------------------------------------------------------------

. 
. ***Female       
. medeff (regress competent1 conciliatory democrat hostsexism benevsexism secordersexism hawkish female_respondent po
> litical_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 competent1 concil
> iatory democrat hostsexism benevsexism hawkish female_respondent political_identfication education hhi age white Se
> xismOrder nonwhite_placebo) if female==1, mediate(competent1) treat(conciliatory) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       416
-------------+----------------------------------   F(14, 401)      =      7.21
       Model |  210.203933        14  15.0145666   Prob > F        =    0.0000
    Residual |  834.678279       401  2.08149197   R-squared       =    0.2012
-------------+----------------------------------   Adj R-squared   =    0.1733
       Total |  1044.88221       415  2.51778846   Root MSE        =    1.4427

-----------------------------------------------------------------------------------------
             competent1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -1.204046   .1431511    -8.41   0.000    -1.485466    -.922625
               democrat |  -.1315015   .1424769    -0.92   0.357    -.4115964    .1485934
             hostsexism |   -.297874   .0811881    -3.67   0.000    -.4574814   -.1382665
            benevsexism |    .037073   .0668976     0.55   0.580    -.0944408    .1685868
         secordersexism |  -.0676579     .07008    -0.97   0.335    -.2054281    .0701122
                hawkish |  -.1311324   .0878614    -1.49   0.136    -.3038588    .0415941
      female_respondent |  -.2542789   .1498333    -1.70   0.090    -.5488358    .0402781
political_identfication |  -.0233627     .03936    -0.59   0.553    -.1007405    .0540151
              education |   .0421523   .0378946     1.11   0.267    -.0323446    .1166493
                    hhi |  -.0002115    .000103    -2.05   0.041     -.000414   -8.94e-06
                    age |   .0011492   .0044884     0.26   0.798    -.0076745     .009973
                  white |   -.128591   .1745013    -0.74   0.462    -.4716426    .2144607
            SexismOrder |  -.1248315   .1445662    -0.86   0.388    -.4090339    .1593709
       nonwhite_placebo |  -.0945068   .1615512    -0.58   0.559    -.4120999    .2230863
                  _cons |   7.063616   .5525657    12.78   0.000     5.977329    8.149904
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       416
-------------+----------------------------------   F(14, 401)      =     43.45
       Model |   711.13924        14    50.79566   Prob > F        =    0.0000
    Residual |  468.774222       401  1.16901302   R-squared       =    0.6027
-------------+----------------------------------   Adj R-squared   =    0.5888
       Total |  1179.91346       415  2.84316497   Root MSE        =    1.0812

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .7754783    .116078     6.68   0.000      .547281    1.003676
             competent1 |  -.6971045   .0373806   -18.65   0.000    -.7705909   -.6236181
               democrat |  -.1611996   .1068664    -1.51   0.132    -.3712879    .0488887
             hostsexism |   .0196421   .0604441     0.32   0.745    -.0991848    .1384689
            benevsexism |   .0087627    .048362     0.18   0.856    -.0863119    .1038374
                hawkish |   .0146237   .0659875     0.22   0.825     -.115101    .1443484
      female_respondent |  -.0190525   .1126884    -0.17   0.866    -.2405863    .2024813
political_identfication |   .0251693    .029508     0.85   0.394    -.0328404     .083179
              education |   .0215688   .0283766     0.76   0.448    -.0342168    .0773544
                    hhi |  -.0000954   .0000776    -1.23   0.219     -.000248    .0000571
                    age |     .00048   .0033626     0.14   0.887    -.0061306    .0070905
                  white |   .0652293    .130622     0.50   0.618    -.1915601    .3220186
            SexismOrder |   .1663277   .1080986     1.54   0.125     -.046183    .3788384
       nonwhite_placebo |  -.0336173   .1210587    -0.28   0.781    -.2716064    .2043718
                  _cons |   5.962419     .45038    13.24   0.000     5.077018     6.84782
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .8373216      .5983946      1.093995
        Direct Effect          |  .7803213      .5552874      1.011029
        Total Effect           |  1.617643      1.532282       1.70043
        % of Tot Eff mediated  |  .5169276      .4924177      .5464541
------------------------------------------------------------------------------------

. 
. 
. ********************************************************************************
. *                                                TABLE 2: STUDY 1 REPUBLICANS                                      
>         *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Binary DV, Full Sample
. reg disapproval1_binary 1.femsq 1.femsq#republican_respondent 1.femconc 1.femconc#republican_respondent 1.malesq 1.
> malesq#republican_respondent 1.maleconc 1.maleconc#republican_respondent, robust noconst

Linear regression                               Number of obs     =        892
                                                F(8, 884)         =      59.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4220
                                                Root MSE          =     .36877

------------------------------------------------------------------------------------------------
                               |               Robust
           disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
                       1.femsq |   .0833333   .0222284     3.75   0.000     .0397066      .12696
                               |
   femsq#republican_respondent |
                          1 1  |  -.0277778   .0350633    -0.79   0.428    -.0965949    .0410393
                               |
                     1.femconc |   .2582781   .0357793     7.22   0.000     .1880558    .3285005
                               |
 femconc#republican_respondent |
                          1 1  |   .5163697    .061328     8.42   0.000     .3960043    .6367352
                               |
                      1.malesq |   .1045752   .0248507     4.21   0.000     .0558018    .1533485
                               |
  malesq#republican_respondent |
                          1 1  |  -.0031259    .044166    -0.07   0.944    -.0898083    .0835566
                               |
                    1.maleconc |   .2162162   .0339913     6.36   0.000     .1495032    .2829293
                               |
maleconc#republican_respondent |
                          1 1  |   .3671171   .0675406     5.44   0.000     .2345585    .4996757
------------------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Republican Respondent)
. lincom (1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.maleco
> nc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.republican_respondent + 1.femconc + 1.femconc#1.republican_respondent + 1.malesq +
       1.malesq#1.republican_respondent - 1.maleconc - 1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2372083   .0891947     2.66   0.008     .0621502    .4122663
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Republican Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0633038   .0595586     1.06   0.288    -.0535891    .1801966
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.malec
> onc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.ma
> lesq))

 ( 1)  - 1.femsq#1.republican_respondent + 1.femconc#1.republican_respondent + 1.malesq#1.republican_respondent -
       1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1739045   .1072517     1.62   0.105    -.0365931    .3844022
------------------------------------------------------------------------------

. 
. ***Model 2: 7-Point DV, Full Sample
. reg disapproval1 1.femsq 1.femsq#republican_respondent 1.femconc 1.femconc#republican_respondent 1.malesq 1.malesq#
> republican_respondent 1.maleconc 1.maleconc#republican_respondent, robust noconst

Linear regression                               Number of obs     =        892
                                                F(8, 884)         =     619.24
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8537
                                                Root MSE          =     1.4386

------------------------------------------------------------------------------------------------
                               |               Robust
                  disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
                       1.femsq |   2.826923   .1038942    27.21   0.000     2.623015    3.030831
                               |
   femsq#republican_respondent |
                          1 1  |  -.6463675   .1709324    -3.78   0.000    -.9818481   -.3108869
                               |
                     1.femconc |   3.682119   .1220753    30.16   0.000     3.442528     3.92171
                               |
 femconc#republican_respondent |
                          1 1  |   1.655909   .2220559     7.46   0.000     1.220091    2.091727
                               |
                      1.malesq |   2.816993   .1104238    25.51   0.000      2.60027    3.033717
                               |
  malesq#republican_respondent |
                          1 1  |  -.0923558   .2106164    -0.44   0.661    -.5057223    .3210107
                               |
                    1.maleconc |   3.439189   .1164669    29.53   0.000     3.210605    3.667773
                               |
maleconc#republican_respondent |
                          1 1  |   1.185811   .2442776     4.85   0.000     .7063792    1.665242
------------------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Republican Respondent)
. lincom (1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.maleco
> nc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.republican_respondent + 1.femconc + 1.femconc#1.republican_respondent + 1.malesq +
       1.malesq#1.republican_respondent - 1.maleconc - 1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    1.25711   .3620817     3.47   0.001     .5464702     1.96775
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Republican Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2330004   .2268355     1.03   0.305    -.2121985    .6781993
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.malec
> onc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.ma
> lesq))

 ( 1)  - 1.femsq#1.republican_respondent + 1.femconc#1.republican_respondent + 1.malesq#1.republican_respondent -
       1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    1.02411   .4272675     2.40   0.017     .1855329    1.862687
------------------------------------------------------------------------------

. 
. ***Model 3: Binary DV, Attentive Sample
. reg disapproval1_binary 1.femsq 1.femsq#republican_respondent 1.femconc 1.femconc#republican_respondent 1.malesq 1.
> malesq#republican_respondent 1.maleconc 1.maleconc#republican_respondent if policy_manipcheck==1 & name_manipcheck=
> =1, robust noconst

Linear regression                               Number of obs     =        514
                                                F(8, 506)         =      56.71
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5057
                                                Root MSE          =     .36584

------------------------------------------------------------------------------------------------
                               |               Robust
           disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
                       1.femsq |   .0853659   .0311003     2.74   0.006     .0242642    .1464676
                               |
   femsq#republican_respondent |
                          1 1  |  -.0490022   .0401798    -1.22   0.223    -.1279421    .0299376
                               |
                     1.femconc |   .2988506   .0494628     6.04   0.000     .2016728    .3960284
                               |
 femconc#republican_respondent |
                          1 1  |   .5530013   .0694303     7.96   0.000     .4165942    .6894084
                               |
                      1.malesq |   .0941176   .0319204     2.95   0.003     .0314048    .1568305
                               |
  malesq#republican_respondent |
                          1 1  |  -.0107843   .0563416    -0.19   0.848    -.1214765    .0999079
                               |
                    1.maleconc |   .2702703    .052032     5.19   0.000     .1680449    .3724957
                               |
maleconc#republican_respondent |
                          1 1  |   .3394858   .0927515     3.66   0.000     .1572604    .5217112
------------------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Republican Respondent)
. lincom (1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.maleco
> nc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.republican_respondent + 1.femconc + 1.femconc#1.republican_respondent + 1.malesq +
       1.malesq#1.republican_respondent - 1.maleconc - 1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2890655   .1052243     2.75   0.006     .0823352    .4957957
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Republican Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0373321   .0844988     0.44   0.659    -.1286796    .2033438
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.malec
> onc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.ma
> lesq))

 ( 1)  - 1.femsq#1.republican_respondent + 1.femconc#1.republican_respondent + 1.malesq#1.republican_respondent -
       1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2517334   .1349526     1.87   0.063     -.013403    .5168697
------------------------------------------------------------------------------

. 
. ***Model 4: 7-Point DV, Attentive Sample
. reg disapproval1 1.femsq 1.femsq#republican_respondent 1.femconc 1.femconc#republican_respondent 1.malesq 1.malesq#
> republican_respondent 1.maleconc 1.maleconc#republican_respondent if policy_manipcheck==1 & name_manipcheck==1, rob
> ust noconst

Linear regression                               Number of obs     =        514
                                                F(8, 506)         =     383.68
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8629
                                                Root MSE          =     1.4198

------------------------------------------------------------------------------------------------
                               |               Robust
                  disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
                       1.femsq |   2.682927   .1345059    19.95   0.000     2.418668    2.947186
                               |
   femsq#republican_respondent |
                          1 1  |  -.5192905   .1968578    -2.64   0.009    -.9060498   -.1325311
                               |
                     1.femconc |   3.747126   .1688503    22.19   0.000     3.415392     4.07886
                               |
 femconc#republican_respondent |
                          1 1  |   1.734355    .256812     6.75   0.000     1.229806    2.238904
                               |
                      1.malesq |   2.741176   .1453702    18.86   0.000     2.455573     3.02678
                               |
  malesq#republican_respondent |
                          1 1  |  -.4356209   .2694077    -1.62   0.107    -.9649164    .0936746
                               |
                    1.maleconc |   3.527027   .1798892    19.61   0.000     3.173605    3.880449
                               |
maleconc#republican_respondent |
                          1 1  |   1.351022   .3315795     4.07   0.000     .6995797    2.002464
------------------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Republican Respondent)
. lincom (1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.maleco
> nc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.republican_respondent + 1.femconc + 1.femconc#1.republican_respondent + 1.malesq +
       1.malesq#1.republican_respondent - 1.maleconc - 1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7453519   .4325922     1.72   0.086    -.1045462     1.59525
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Republican Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2783491   .3163777     0.88   0.379    -.3432267    .8999248
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.malec
> onc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.ma
> lesq))

 ( 1)  - 1.femsq#1.republican_respondent + 1.femconc#1.republican_respondent + 1.malesq#1.republican_respondent -
       1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4670028   .5359393     0.87   0.384    -.5859374    1.519943
------------------------------------------------------------------------------

. 
. 
. ********************************************************************************
. *                                TABLE A-6: STUDY 1 HETEROGENEOUS EFFECTS                                          
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Republican Respondent
. eststo: reg disapproval1 1.femsq 1.femsq#republican_respondent 1.femconc 1.femconc#republican_respondent 1.malesq 1
> .malesq#republican_respondent 1.maleconc 1.maleconc#republican_respondent democrat hostsexism benevsexism secorders
> exism hawkish female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robus
> t noconst

Linear regression                               Number of obs     =        813
                                                F(21, 792)        =     217.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8529
                                                Root MSE          =     1.4431

------------------------------------------------------------------------------------------------
                               |               Robust
                  disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
                       1.femsq |   2.192145   .4310582     5.09   0.000     1.345993    3.038297
                               |
   femsq#republican_respondent |
                          1 1  |  -1.137331   .2497961    -4.55   0.000    -1.627672   -.6469908
                               |
                     1.femconc |    3.07397   .4159814     7.39   0.000     2.257413    3.890526
                               |
 femconc#republican_respondent |
                          1 1  |   1.088764   .2906706     3.75   0.000     .5181877     1.65934
                               |
                      1.malesq |   2.175186   .4377102     4.97   0.000     1.315977    3.034396
                               |
  malesq#republican_respondent |
                          1 1  |  -.5397454   .2726446    -1.98   0.048    -1.074937    -.004554
                               |
                    1.maleconc |   2.810533   .4293447     6.55   0.000     1.967744    3.653321
                               |
maleconc#republican_respondent |
                          1 1  |   .6463098   .2964462     2.18   0.030     .0643967    1.228223
                               |
                      democrat |   .0061994   .1024644     0.06   0.952    -.1949345    .2073332
                    hostsexism |   .0646234   .0640514     1.01   0.313    -.0611072     .190354
                   benevsexism |  -.1020581   .0545027    -1.87   0.062    -.2090449    .0049286
                secordersexism |   .0965103   .0552514     1.75   0.081    -.0119461    .2049667
                       hawkish |   .0693881   .0712742     0.97   0.331    -.0705205    .2092967
             female_respondent |   .0239192   .1043371     0.23   0.819    -.1808907    .2287291
       political_identfication |   .1023854   .0475072     2.16   0.031     .0091305    .1956404
                     education |  -.0318022   .0261336    -1.22   0.224    -.0831015    .0194971
                           hhi |   .0000216     .00008     0.27   0.788    -.0001356    .0001787
                           age |   .0019114    .003103     0.62   0.538    -.0041796    .0080023
                         white |   .0386289   .1258756     0.31   0.759    -.2084604    .2857181
                   SexismOrder |  -.0952973   .1042406    -0.91   0.361    -.2999178    .1093232
              nonwhite_placebo |  -.0357061   .1267824    -0.28   0.778    -.2845755    .2131632
------------------------------------------------------------------------------------------------
(est1 stored)

. 
. *Gendered Peace Premium (Republican Respondent)
. lincom (1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.maleco
> nc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.republican_respondent + 1.femconc + 1.femconc#1.republican_respondent + 1.malesq +
       1.malesq#1.republican_respondent - 1.maleconc - 1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.286518   .3818325     3.37   0.001     .5369949    2.036042
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Republican Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2464784   .2432903     1.01   0.311    -.2310916    .7240483
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.malec
> onc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.ma
> lesq))

 ( 1)  - 1.femsq#1.republican_respondent + 1.femconc#1.republican_respondent + 1.malesq#1.republican_respondent -
       1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    1.04004   .4595528     2.26   0.024     .1379544    1.942125
------------------------------------------------------------------------------

. 
. 
. ***Model 2: Hostile Sexism 
. eststo: reg disapproval1 1.femsq 1.femsq#hostsexismIQR 1.femconc 1.femconc#hostsexismIQR 1.malesq 1.malesq#hostsexi
> smIQR 1.maleconc 1.maleconc#hostsexismIQR democrat republican_respondent benevsexism secordersexism hawkish female_
> respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        556
                                                F(21, 535)        =     131.16
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8377
                                                Root MSE          =     1.5699

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   1.574949   .5189066     3.04   0.003     .5556049    2.594293
                        |
    femsq#hostsexismIQR |
                   1 1  |    .161893   .2688853     0.60   0.547    -.3663074    .6900934
                        |
              1.femconc |     2.8033   .5026509     5.58   0.000     1.815889    3.790712
                        |
  femconc#hostsexismIQR |
                   1 1  |    .828246   .3017805     2.74   0.006     .2354259    1.421066
                        |
               1.malesq |   2.307573    .514527     4.48   0.000     1.296832    3.318314
                        |
   malesq#hostsexismIQR |
                   1 1  |  -.5268067   .2852697    -1.85   0.065    -1.087193    .0335794
                        |
             1.maleconc |   2.775474   .5008233     5.54   0.000     1.791653    3.759295
                        |
 maleconc#hostsexismIQR |
                   1 1  |   .3325319   .2988637     1.11   0.266    -.2545583    .9196221
                        |
               democrat |   .0228335   .1343301     0.17   0.865    -.2410456    .2867126
  republican_respondent |   .0710555   .2639159     0.27   0.788    -.4473829    .5894939
            benevsexism |  -.0942594   .0673622    -1.40   0.162    -.2265862    .0380674
         secordersexism |   .1335384   .0719926     1.85   0.064    -.0078846    .2749613
                hawkish |   .0595942   .0916859     0.65   0.516    -.1205142    .2397027
      female_respondent |   .0367411   .1399552     0.26   0.793    -.2381881    .3116703
political_identfication |    .085946   .0614486     1.40   0.162     -.034764    .2066561
              education |  -.0201652   .0365977    -0.55   0.582     -.092058    .0517277
                    hhi |    .000056   .0001051     0.53   0.595    -.0001505    .0002624
                    age |   .0037898   .0042875     0.88   0.377    -.0046327    .0122123
                  white |   .1939038   .1634091     1.19   0.236    -.1270983    .5149059
            SexismOrder |  -.1543317   .1360221    -1.13   0.257    -.4215347    .1128712
       nonwhite_placebo |   .0909826   .1745848     0.52   0.602    -.2519733    .4339384
-----------------------------------------------------------------------------------------
(est2 stored)

. 
. *Gendered Peace Premium (Sexist Respondent)
. lincom (1.femconc+1.femconc#1.hostsexismIQR)-(1.femsq+1.femsq#1.hostsexismIQR)-(1.maleconc+1.maleconc#1.hostsexismI
> QR)+(1.malesq+1.malesq#1.hostsexismIQR)

 ( 1)  - 1.femsq - 1.femsq#1.hostsexismIQR + 1.femconc + 1.femconc#1.hostsexismIQR + 1.malesq +
       1.malesq#1.hostsexismIQR - 1.maleconc - 1.maleconc#1.hostsexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5674645   .3479566     1.63   0.104    -.1160642    1.250993
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Sexist Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7604501     .42267     1.80   0.073    -.0698462    1.590746
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hostsexismIQR)-(1.femsq+1.femsq#1.hostsexismIQR)-(1.maleconc+1.maleconc#1.hostsexism
> IQR)+(1.malesq+1.malesq#1.hostsexismIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hostsexismIQR + 1.femconc#1.hostsexismIQR + 1.malesq#1.hostsexismIQR - 1.maleconc#1.hostsexismIQR
       = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.1929856   .5515288    -0.35   0.727    -1.276413     .890442
------------------------------------------------------------------------------

. 
. 
. ***Model 3: Benevolent Sexism 
. eststo: reg disapproval1 1.femsq 1.femsq#benevsexismIQR 1.femconc 1.femconc#benevsexismIQR 1.malesq 1.malesq#benevs
> exismIQR 1.maleconc 1.maleconc#benevsexismIQR democrat republican_respondent hostsexism secordersexism hawkish fema
> le_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        525
                                                F(21, 504)        =     119.07
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8323
                                                Root MSE          =     1.5313

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   1.033295   .4867941     2.12   0.034        .0769    1.989691
                        |
   femsq#benevsexismIQR |
                   1 1  |   .1904344   .2379091     0.80   0.424    -.2769813    .6578502
                        |
              1.femconc |    3.02174   .5209104     5.80   0.000     1.998317    4.045164
                        |
 femconc#benevsexismIQR |
                   1 1  |  -.5010392   .3031377    -1.65   0.099    -1.096608      .09453
                        |
               1.malesq |   1.348218   .5246303     2.57   0.010     .3174866     2.37895
                        |
  malesq#benevsexismIQR |
                   1 1  |   .0589956   .2816478     0.21   0.834    -.4943528    .6123441
                        |
             1.maleconc |   2.716121   .5015482     5.42   0.000     1.730738    3.701504
                        |
maleconc#benevsexismIQR |
                   1 1  |  -.5166789   .2929474    -1.76   0.078    -1.092227    .0588696
                        |
               democrat |   -.088594   .1374438    -0.64   0.519    -.3586274    .1814394
  republican_respondent |  -.0763911   .2631259    -0.29   0.772      -.59335    .4405677
             hostsexism |   .1098867   .0796439     1.38   0.168    -.0465883    .2663618
         secordersexism |    .126646   .0649235     1.95   0.052    -.0009081    .2542001
                hawkish |   .1578108   .0899547     1.75   0.080    -.0189217    .3345433
      female_respondent |   .0617902   .1417281     0.44   0.663    -.2166605    .3402408
political_identfication |   .0908538   .0602529     1.51   0.132    -.0275239    .2092316
              education |  -.0785327   .0345508    -2.27   0.023    -.1464141   -.0106513
                    hhi |  -5.62e-06    .000091    -0.06   0.951    -.0001844    .0001732
                    age |   .0030205   .0042415     0.71   0.477    -.0053126    .0113536
                  white |  -.0515859   .1598476    -0.32   0.747    -.3656357    .2624639
            SexismOrder |   -.064017   .1380892    -0.46   0.643    -.3353183    .2072843
       nonwhite_placebo |   .0669995   .1691064     0.40   0.692    -.2652409    .3992399
-----------------------------------------------------------------------------------------
(est3 stored)

. 
. *Gendered Peace Premium (Sexist Respondent)
. lincom (1.femconc+1.femconc#1.benevsexismIQR)-(1.femsq+1.femsq#1.benevsexismIQR)-(1.maleconc+1.maleconc#1.benevsexi
> smIQR)+(1.malesq+1.malesq#1.benevsexismIQR)

 ( 1)  - 1.femsq - 1.femsq#1.benevsexismIQR + 1.femconc + 1.femconc#1.benevsexismIQR + 1.malesq +
       1.malesq#1.benevsexismIQR - 1.maleconc - 1.maleconc#1.benevsexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5047431   .3433466     1.47   0.142    -.1698239     1.17931
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Sexist Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .6205422   .4328808     1.43   0.152    -.2299309    1.471015
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.benevsexismIQR)-(1.femsq+1.femsq#1.benevsexismIQR)-(1.maleconc+1.maleconc#1.benevsex
> ismIQR)+(1.malesq+1.malesq#1.benevsexismIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.benevsexismIQR + 1.femconc#1.benevsexismIQR + 1.malesq#1.benevsexismIQR -
       1.maleconc#1.benevsexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.1157991   .5555412    -0.21   0.835    -1.207261    .9756627
------------------------------------------------------------------------------

. 
. 
. ***Model 4: Second-Order Sexism 
. eststo: reg disapproval1 1.femsq 1.femsq#secordersexismIQR 1.femconc 1.femconc#secordersexismIQR 1.malesq 1.malesq#
> secordersexismIQR 1.maleconc 1.maleconc#secordersexismIQR democrat republican_respondent hostsexism benevsexism haw
> kish female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        597
                                                F(21, 576)        =     142.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8369
                                                Root MSE          =      1.528

--------------------------------------------------------------------------------------------
                           |               Robust
              disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                   1.femsq |   2.413198   .4825224     5.00   0.000      1.46548    3.360916
                           |
   femsq#secordersexismIQR |
                      1 1  |  -.0350982    .257454    -0.14   0.892    -.5407614    .4705649
                           |
                 1.femconc |   3.874003    .490312     7.90   0.000     2.910986    4.837021
                           |
 femconc#secordersexismIQR |
                      1 1  |   .1469137     .27263     0.54   0.590    -.3885563    .6823838
                           |
                  1.malesq |   2.698977   .4740722     5.69   0.000     1.767856    3.630098
                           |
  malesq#secordersexismIQR |
                      1 1  |  -.1014702   .2535012    -0.40   0.689    -.5993696    .3964292
                           |
                1.maleconc |   3.304732   .4921597     6.71   0.000     2.338086    4.271378
                           |
maleconc#secordersexismIQR |
                      1 1  |   .5695005   .2643568     2.15   0.032     .0502796    1.088721
                           |
                  democrat |    -.02846   .1276758    -0.22   0.824    -.2792269     .222307
     republican_respondent |   .0248335   .2453253     0.10   0.919    -.4570077    .5066747
                hostsexism |   .0048639   .0773494     0.06   0.950    -.1470575    .1567852
               benevsexism |  -.1001875   .0633112    -1.58   0.114    -.2245364    .0241614
                   hawkish |   .1039279   .0835019     1.24   0.214    -.0600774    .2679332
         female_respondent |   .0011088   .1297103     0.01   0.993     -.253654    .2558716
   political_identfication |   .1053782   .0594791     1.77   0.077    -.0114443    .2222006
                 education |  -.0609521   .0322532    -1.89   0.059    -.1243002    .0023961
                       hhi |   .0000826    .000094     0.88   0.380    -.0001021    .0002673
                       age |   .0042061   .0037231     1.13   0.259    -.0031064    .0115186
                     white |  -.0583526   .1531726    -0.38   0.703    -.3591975    .2424923
               SexismOrder |   -.146859   .1297933    -1.13   0.258    -.4017849    .1080669
          nonwhite_placebo |  -.0250359   .1576149    -0.16   0.874    -.3346059     .284534
--------------------------------------------------------------------------------------------
(est4 stored)

. 
. *Gendered Peace Premium (Sexist Respondent)
. lincom (1.femconc+1.femconc#1.secordersexismIQR)-(1.femsq+1.femsq#1.secordersexismIQR)-(1.maleconc+1.maleconc#1.sec
> ordersexismIQR)+(1.malesq+1.malesq#1.secordersexismIQR)

 ( 1)  - 1.femsq - 1.femsq#1.secordersexismIQR + 1.femconc + 1.femconc#1.secordersexismIQR + 1.malesq +
       1.malesq#1.secordersexismIQR - 1.maleconc - 1.maleconc#1.secordersexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3660917   .3950543     0.93   0.354    -.4098308    1.142014
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Sexist Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .8550505    .324962     2.63   0.009     .2167955    1.493306
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.secordersexismIQR)-(1.femsq+1.femsq#1.secordersexismIQR)-(1.maleconc+1.maleconc#1.se
> cordersexismIQR)+(1.malesq+1.malesq#1.secordersexismIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.secordersexismIQR + 1.femconc#1.secordersexismIQR + 1.malesq#1.secordersexismIQR -
       1.maleconc#1.secordersexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.4889587   .5140973    -0.95   0.342    -1.498693    .5207751
------------------------------------------------------------------------------

. 
. 
. ***Model 5: Militant Assertiveness 
. eststo: reg disapproval1 1.femsq 1.femsq#hawkishIQR 1.femconc 1.femconc#hawkishIQR 1.malesq 1.malesq#hawkishIQR 1.m
> aleconc 1.maleconc#hawkishIQR democrat republican_respondent hostsexism benevsexism secordersexism female_responden
> t political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        526
                                                F(21, 505)        =     136.93
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8508
                                                Root MSE          =     1.4696

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   2.457324   .5508424     4.46   0.000     1.375099    3.539549
                        |
       femsq#hawkishIQR |
                   1 1  |  -.8618745   .2449166    -3.52   0.000    -1.343055   -.3806936
                        |
              1.femconc |   2.881761   .5543105     5.20   0.000     1.792722      3.9708
                        |
     femconc#hawkishIQR |
                   1 1  |   1.351903   .2851478     4.74   0.000      .791681    1.912125
                        |
               1.malesq |    2.80501    .546931     5.13   0.000      1.73047    3.879551
                        |
      malesq#hawkishIQR |
                   1 1  |  -1.237362   .2817238    -4.39   0.000    -1.790857   -.6838664
                        |
             1.maleconc |   2.848601    .528489     5.39   0.000     1.810293    3.886909
                        |
    maleconc#hawkishIQR |
                   1 1  |    .923242   .2737936     3.37   0.001     .3853272    1.461157
                        |
               democrat |  -.0533437   .1306969    -0.41   0.683    -.3101202    .2034329
  republican_respondent |   .3596772   .2673067     1.35   0.179    -.1654929    .8848473
             hostsexism |   .1606053   .0810079     1.98   0.048     .0014513    .3197594
            benevsexism |  -.1162199   .0628687    -1.85   0.065    -.2397363    .0072965
         secordersexism |   .1229022   .0700635     1.75   0.080    -.0147497     .260554
      female_respondent |   .0540168   .1352935     0.40   0.690    -.2117906    .3198243
political_identfication |   .0332212   .0629431     0.53   0.598    -.0904413    .1568837
              education |  -.0516981   .0345588    -1.50   0.135    -.1195947    .0161985
                    hhi |      .0001   .0000896     1.12   0.265     -.000076     .000276
                    age |   .0005438   .0038963     0.14   0.889    -.0071112    .0081987
                  white |   .0449535   .1607187     0.28   0.780    -.2708061    .3607131
            SexismOrder |  -.1834913    .133279    -1.38   0.169    -.4453409    .0783583
       nonwhite_placebo |  -.0267782   .1610413    -0.17   0.868    -.3431717    .2896153
-----------------------------------------------------------------------------------------
(est5 stored)

. 
. *Gendered Peace Premium (Hawkish Respondent)
. lincom (1.femconc+1.femconc#1.hawkishIQR)-(1.femsq+1.femsq#1.hawkishIQR)-(1.maleconc+1.maleconc#1.hawkishIQR)+(1.ma
> lesq+1.malesq#1.hawkishIQR)

 ( 1)  - 1.femsq - 1.femsq#1.hawkishIQR + 1.femconc + 1.femconc#1.hawkishIQR + 1.malesq + 1.malesq#1.hawkishIQR -
       1.maleconc - 1.maleconc#1.hawkishIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4340196   .3645256     1.19   0.234    -.2821539    1.150193
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Hawkish Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3808457   .3645915     1.04   0.297    -.3354572    1.097149
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hawkishIQR)-(1.femsq+1.femsq#1.hawkishIQR)-(1.maleconc+1.maleconc#1.hawkishIQR)+(1.m
> alesq+1.malesq#1.hawkishIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hawkishIQR + 1.femconc#1.hawkishIQR + 1.malesq#1.hawkishIQR - 1.maleconc#1.hawkishIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .053174   .5182053     0.10   0.918    -.9649297    1.071278
------------------------------------------------------------------------------

. 
. 
. ***Model 6: Education 
. eststo: reg disapproval1 1.femsq 1.femsq#educationIQR 1.femconc 1.femconc#educationIQR 1.malesq 1.malesq#educationI
> QR 1.maleconc 1.maleconc#educationIQR democrat republican_respondent hostsexism benevsexism secordersexism hawkish 
> female_respondent political_identfication hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        562
                                                F(21, 541)        =     137.68
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8422
                                                Root MSE          =     1.4878

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   1.411286   .5345424     2.64   0.009      .361253    2.461319
                        |
     femsq#educationIQR |
                   1 1  |  -.3424734    .246545    -1.39   0.165    -.8267761    .1418294
                        |
              1.femconc |   2.608909   .5240969     4.98   0.000     1.579395    3.638423
                        |
   femconc#educationIQR |
                   1 1  |   .3081962   .2755536     1.12   0.264    -.2330898    .8494823
                        |
               1.malesq |   1.513498    .524084     2.89   0.004      .484009    2.542987
                        |
    malesq#educationIQR |
                   1 1  |  -.3036828   .2370762    -1.28   0.201    -.7693856    .1620199
                        |
             1.maleconc |   2.367928   .5476034     4.32   0.000     1.292239    3.443618
                        |
  maleconc#educationIQR |
                   1 1  |  -.0178022   .2830278    -0.06   0.950    -.5737703    .5381659
                        |
               democrat |  -.0864077   .1271955    -0.68   0.497    -.3362652    .1634499
  republican_respondent |   .1303219   .2400745     0.54   0.587    -.3412704    .6019143
             hostsexism |   .1203345    .081729     1.47   0.142    -.0402105    .2808795
            benevsexism |  -.0798196   .0661995    -1.21   0.228    -.2098591      .05022
         secordersexism |   .1291052   .0655646     1.97   0.049     .0003128    .2578976
                hawkish |   .0902355   .0888042     1.02   0.310    -.0842078    .2646789
      female_respondent |   .1816005   .1284579     1.41   0.158    -.0707368    .4339378
political_identfication |   .0757985   .0582102     1.30   0.193    -.0385473    .1901443
                    hhi |   .0001155   .0000929     1.24   0.215    -.0000671    .0002981
                    age |   .0023434   .0039515     0.59   0.553    -.0054186    .0101055
                  white |   .0330067   .1512038     0.22   0.827    -.2640117    .3300251
            SexismOrder |  -.0352929   .1287713    -0.27   0.784    -.2882459      .21766
       nonwhite_placebo |  -.0034224   .1569995    -0.02   0.983    -.3118258     .304981
-----------------------------------------------------------------------------------------
(est6 stored)

. 
. *Gendered Peace Premium (Educated Respondent)
. lincom (1.femconc+1.femconc#1.educationIQR)-(1.femsq+1.femsq#1.educationIQR)-(1.maleconc+1.maleconc#1.educationIQR)
> +(1.malesq+1.malesq#1.educationIQR)

 ( 1)  - 1.femsq - 1.femsq#1.educationIQR + 1.femconc + 1.femconc#1.educationIQR + 1.malesq + 1.malesq#1.educationIQR
       - 1.maleconc - 1.maleconc#1.educationIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7079817   .3330627     2.13   0.034      .053727    1.362236
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Uneducated Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3431927   .3979824     0.86   0.389    -.4385875    1.124973
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.educationIQR)-(1.femsq+1.femsq#1.educationIQR)-(1.maleconc+1.maleconc#1.educationIQR
> )+(1.malesq+1.malesq#1.educationIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.educationIQR + 1.femconc#1.educationIQR + 1.malesq#1.educationIQR - 1.maleconc#1.educationIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .364789   .5206674     0.70   0.484    -.6579886    1.387567
------------------------------------------------------------------------------

. 
. 
. ***Model 7: Female Respondents
. eststo: reg disapproval1 1.femsq 1.femsq#female_respondent 1.femconc 1.femconc#female_respondent 1.malesq 1.malesq#
> female_respondent 1.maleconc 1.maleconc#female_respondent democrat republican_respondent hostsexism benevsexism sec
> ordersexism hawkish political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        813
                                                F(21, 792)        =     200.45
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8414
                                                Root MSE          =     1.4984

--------------------------------------------------------------------------------------------
                           |               Robust
              disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                   1.femsq |   1.406182   .4521538     3.11   0.002       .51862    2.293743
                           |
   femsq#female_respondent |
                      1 1  |   .3675371   .1915305     1.92   0.055    -.0084304    .7435045
                           |
                 1.femconc |   3.325771   .4588956     7.25   0.000     2.424976    4.226567
                           |
 femconc#female_respondent |
                      1 1  |   -.234665   .2266283    -1.04   0.301    -.6795281     .210198
                           |
                  1.malesq |   1.694264   .4422358     3.83   0.000     .8261706    2.562357
                           |
  malesq#female_respondent |
                      1 1  |   .1763767    .211502     0.83   0.405     -.238794    .5915474
                           |
                1.maleconc |    2.90487   .4462262     6.51   0.000     2.028944    3.780795
                           |
maleconc#female_respondent |
                      1 1  |  -.1818248   .2266855    -0.80   0.423    -.6268002    .2631507
                           |
                  democrat |   .0019018   .1060368     0.02   0.986    -.2062446    .2100482
     republican_respondent |   .0147914   .2023421     0.07   0.942    -.3823989    .4119817
                hostsexism |   .1170949   .0668314     1.75   0.080    -.0140928    .2482826
               benevsexism |  -.0676344   .0568705    -1.19   0.235    -.1792692    .0440003
            secordersexism |   .0970048   .0575315     1.69   0.092    -.0159273     .209937
                   hawkish |   .0614295   .0733448     0.84   0.403    -.0825437    .2054028
   political_identfication |   .0917416   .0490677     1.87   0.062    -.0045766    .1880598
                 education |   -.035635   .0273333    -1.30   0.193    -.0892892    .0180192
                       hhi |   .0000697    .000081     0.86   0.390    -.0000893    .0002286
                       age |   .0021699   .0032223     0.67   0.501    -.0041553    .0084951
                     white |   .0457667   .1283813     0.36   0.722    -.2062412    .2977746
               SexismOrder |  -.0576873   .1077055    -0.54   0.592    -.2691094    .1537347
          nonwhite_placebo |  -.0067098   .1333937    -0.05   0.960    -.2685569    .2551373
--------------------------------------------------------------------------------------------
(est7 stored)

. 
. *Gendered Peace Premium (Female Respondent)
. lincom (1.femconc+1.femconc#1.female_respondent)-(1.femsq+1.femsq#1.female_respondent)-(1.maleconc+1.maleconc#1.fem
> ale_respondent)+(1.malesq+1.malesq#1.female_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.female_respondent + 1.femconc + 1.femconc#1.female_respondent + 1.malesq +
       1.malesq#1.female_respondent - 1.maleconc - 1.maleconc#1.female_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .464983   .2922343     1.59   0.112    -.1086623    1.038628
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Male Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7089836   .3073441     2.31   0.021     .1056783    1.312289
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.female_respondent)-(1.femsq+1.femsq#1.female_respondent)-(1.maleconc+1.maleconc#1.fe
> male_respondent)+(1.malesq+1.malesq#1.female_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.female_respondent + 1.femconc#1.female_respondent + 1.malesq#1.female_respondent -
       1.maleconc#1.female_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.2440006   .4259958    -0.57   0.567    -1.080215    .5922137
------------------------------------------------------------------------------

. 
. ********************************************************************************
. *                                TABLE A-7: STUDY 1 CO- AND OUT-PARTISANS                                          
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Co-Partisans
. 
. reg disapproval1 femsq femconc malesq maleconc democrat hostsexism benevsexism secordersexism hawkish female_respon
> dent political_identfication education hhi age white SexismOrder nonwhite_placebo if in_partisan==1, robust noconst

Linear regression                               Number of obs     =        331
                                                F(17, 314)        =      94.30
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8379
                                                Root MSE          =     1.4223

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  femsq |    .008315   .8118267     0.01   0.992    -1.588993    1.605623
                femconc |   1.870411   .8216077     2.28   0.023     .2538585    3.486963
                 malesq |   .3753921   .8080146     0.46   0.643    -1.214415    1.965199
               maleconc |   1.433958   .8227655     1.74   0.082    -.1848723    3.052789
               democrat |   .5733518   .4441651     1.29   0.198    -.3005642    1.447268
             hostsexism |   .0546769   .1014296     0.54   0.590    -.1448906    .2542444
            benevsexism |  -.0107865   .0819277    -0.13   0.895    -.1719831    .1504101
         secordersexism |   .1362582   .0822907     1.66   0.099    -.0256527    .2981691
                hawkish |   .1887385   .1166548     1.62   0.107    -.0407853    .4182624
      female_respondent |    .126793   .1636206     0.77   0.439    -.1951382    .4487243
political_identfication |   .2016018   .0968896     2.08   0.038     .0109668    .3922367
              education |  -.0442626   .0405472    -1.09   0.276    -.1240411    .0355159
                    hhi |   .0002755   .0001306     2.11   0.036     .0000185    .0005326
                    age |   .0038835   .0048745     0.80   0.426    -.0057072    .0134743
                  white |  -.1178964   .1946259    -0.61   0.545    -.5008321    .2650394
            SexismOrder |   -.229494   .1630077    -1.41   0.160    -.5502194    .0912314
       nonwhite_placebo |  -.1535566   .2106775    -0.73   0.467    -.5680746    .2609614
-----------------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .8035298   .3268691     2.46   0.015     .1603992     1.44666
------------------------------------------------------------------------------

. 
. ***Model 2: Out-Partisans
. 
. reg disapproval1 femsq femconc malesq maleconc democrat hostsexism benevsexism secordersexism hawkish female_respon
> dent political_identfication education hhi age white SexismOrder nonwhite_placebo if out_partisan==1, robust nocons
> t

Linear regression                               Number of obs     =        312
                                                F(17, 295)        =     107.23
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8512
                                                Root MSE          =     1.5894

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  femsq |   1.904275   .7601369     2.51   0.013     .4082969    3.400254
                femconc |   3.707417   .7629501     4.86   0.000     2.205902    5.208932
                 malesq |   1.999059   .7781563     2.57   0.011      .467618      3.5305
               maleconc |    3.08403   .7744393     3.98   0.000     1.559904    4.608156
               democrat |   .5675845   .4656661     1.22   0.224    -.3488642    1.484033
             hostsexism |   .0331764   .1064395     0.31   0.755    -.1763006    .2426534
            benevsexism |  -.1195627   .1013424    -1.18   0.239    -.3190084    .0798829
         secordersexism |   .1360873   .1065399     1.28   0.202    -.0735873     .345762
                hawkish |   .0779905   .1123699     0.69   0.488    -.1431578    .2991389
      female_respondent |   -.045842   .1876876    -0.24   0.807    -.4152184    .3235343
political_identfication |   .0112276   .1110656     0.10   0.920    -.2073538    .2298089
              education |  -.0185765   .0491569    -0.38   0.706    -.1153192    .0781661
                    hhi |  -.0001376   .0001389    -0.99   0.323     -.000411    .0001358
                    age |    .006168   .0058238     1.06   0.290    -.0052934    .0176293
                  white |    .096966   .2328574     0.42   0.677    -.3613063    .5552382
            SexismOrder |  -.1837271   .1839195    -1.00   0.319    -.5456877    .1782335
       nonwhite_placebo |  -.0360704   .2046645    -0.18   0.860     -.438858    .3667172
-----------------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7181705   .3651158     1.97   0.050    -.0003913    1.436732
------------------------------------------------------------------------------

. 
. ***Model 3: Co- vs. Out-Partisans
. 
. eststo: reg disapproval1 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partis
> an 1.maleconc 1.maleconc#out_partisan democrat republican_respondent hostsexism benevsexism secordersexism hawkish 
> female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =        813
                                                F(22, 791)        =     197.91
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8448
                                                Root MSE          =     1.4833

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   1.205686    .434149     2.78   0.006     .3534659    2.057907
                        |
     femsq#out_partisan |
                   1 1  |   .4939812   .2032906     2.43   0.015     .0949284     .893034
                        |
              1.femconc |   2.710659   .4354728     6.22   0.000      1.85584    3.565478
                        |
   femconc#out_partisan |
                   1 1  |   .7717893   .2273407     3.39   0.001      .325527    1.218052
                        |
               1.malesq |   1.444461   .4371487     3.30   0.001     .5863527     2.30257
                        |
    malesq#out_partisan |
                   1 1  |    .356613   .2249948     1.58   0.113    -.0850445    .7982704
                        |
             1.maleconc |     2.4149   .4405229     5.48   0.000     1.550168    3.279632
                        |
  maleconc#out_partisan |
                   1 1  |   .5103006   .2468757     2.07   0.039     .0256916    .9949096
                        |
               democrat |   .0682346   .1076569     0.63   0.526    -.1430925    .2795617
  republican_respondent |  -.3643725   .2148902    -1.70   0.090    -.7861949      .05745
             hostsexism |    .106303   .0651532     1.63   0.103    -.0215906    .2341967
            benevsexism |  -.0690338   .0563416    -1.23   0.221    -.1796306     .041563
         secordersexism |   .1064308   .0561939     1.89   0.059     -.003876    .2167377
                hawkish |   .0483247   .0731944     0.66   0.509    -.0953536     .192003
      female_respondent |   .0155165   .1065958     0.15   0.884    -.1937277    .2247606
political_identfication |   .1736411   .0516718     3.36   0.001     .0722111    .2750711
              education |   -.031667   .0271162    -1.17   0.243    -.0848952    .0215613
                    hhi |   .0000574   .0000776     0.74   0.459    -.0000948    .0002097
                    age |   .0025414   .0031919     0.80   0.426    -.0037242    .0088069
                  white |   .0307665    .126617     0.24   0.808    -.2177785    .2793114
            SexismOrder |  -.0635187   .1058625    -0.60   0.549    -.2713233     .144286
       nonwhite_placebo |   -.000067   .1298776    -0.00   1.000    -.2550124    .2548785
-----------------------------------------------------------------------------------------
(est1 stored)

. 
. *Gendered Peace Premium (Out-Partisan)
. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .6586549   .3612185     1.82   0.069    -.0504053    1.367715
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Co-Partisan)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5345344   .2523978     2.12   0.035     .0390856    1.029983
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan
> )+(1.malesq+1.malesq#1.out_partisan))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.out_partisan + 1.femconc#1.out_partisan + 1.malesq#1.out_partisan - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1241205   .4398674     0.28   0.778    -.7393249    .9875659
------------------------------------------------------------------------------

. 
. 
. ********************************************************************************
. *                                        TABLE A-8: STUDY 1 GENDER X DEM PRESIDENT                                 
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Binary DV, Full Sample
. eststo: reg disapproval1_binary 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.
> maleconc 1.maleconc#democrat, robust noconst

Linear regression                               Number of obs     =        892
                                                F(8, 884)         =      39.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3303
                                                Root MSE          =     .39696

-----------------------------------------------------------------------------------
                  |               Robust
disapproval1_bi~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |   .0782609   .0251584     3.11   0.002     .0288836    .1276381
                  |
   femsq#democrat |
             1 1  |  -.0074644   .0349339    -0.21   0.831    -.0760275    .0610987
                  |
        1.femconc |   .4070796   .0464253     8.77   0.000     .3159629    .4981964
                  |
 femconc#democrat |
             1 1  |   .0332873   .0666087     0.50   0.617    -.0974424    .1640171
                  |
         1.malesq |   .1192661   .0311834     3.82   0.000     .0580639    .1804682
                  |
  malesq#democrat |
             1 1  |  -.0307705   .0411425    -0.75   0.455    -.1115189     .049978
                  |
       1.maleconc |   .3027523   .0442059     6.85   0.000     .2159915    .3895131
                  |
maleconc#democrat |
             1 1  |   .0666171   .0638097     1.04   0.297     -.058619    .1918532
-----------------------------------------------------------------------------------
(est1 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0886967   .0755424     1.17   0.241    -.0595667    .2369601
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1453325   .0755965     1.92   0.055     -.003037     .293702
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0566358   .1068713    -0.53   0.596     -.266387    .1531153
------------------------------------------------------------------------------

. 
. ***Model 2: 7-Point DV, Full Sample
. eststo: reg disapproval1 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.malecon
> c 1.maleconc#democrat, robust noconst

Linear regression                               Number of obs     =        892
                                                F(8, 884)         =     548.10
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8364
                                                Root MSE          =     1.5213

-----------------------------------------------------------------------------------
                  |               Robust
     disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |   2.721739   .1257025    21.65   0.000     2.475029    2.968449
                  |
   femsq#democrat |
             1 1  |  -.1996152   .1701011    -1.17   0.241    -.5334644    .1342339
                  |
        1.femconc |   4.123894   .1472189    28.01   0.000     3.834955    4.412833
                  |
 femconc#democrat |
             1 1  |   .1788585   .2295071     0.78   0.436    -.2715839    .6293009
                  |
         1.malesq |   2.798165   .1384078    20.22   0.000     2.526519    3.069811
                  |
  malesq#democrat |
             1 1  |  -.0194041     .18897    -0.10   0.918    -.3902863    .3514781
                  |
       1.maleconc |   3.752294   .1575626    23.81   0.000     3.443053    4.061534
                  |
maleconc#democrat |
             1 1  |   .1486073    .223336     0.67   0.506    -.2897234    .5869381
-----------------------------------------------------------------------------------
(est2 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .6584886   .2928129     2.25   0.025     .0837991    1.233178
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4480262   .2854071     1.57   0.117    -.1121283    1.008181
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2104623   .4088968     0.51   0.607    -.5920594    1.012984
------------------------------------------------------------------------------

. 
. ***Model 3: Binary DV, Attentive Sample
. eststo: reg disapproval1_binary 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.
> maleconc 1.maleconc#democrat if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =        514
                                                F(8, 506)         =      30.47
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4138
                                                Root MSE          =     .39838

-----------------------------------------------------------------------------------
                  |               Robust
disapproval1_bi~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |   .0694444   .0301946     2.30   0.022     .0101221    .1287668
                  |
   femsq#democrat |
             1 1  |   -.007906    .042594    -0.19   0.853    -.0915888    .0757769
                  |
        1.femconc |   .4571429   .0600103     7.62   0.000     .3392428     .575043
                  |
 femconc#democrat |
             1 1  |   .1062374   .0843834     1.26   0.209    -.0595476    .2720225
                  |
         1.malesq |   .1052632   .0409689     2.57   0.010      .024773    .1857533
                  |
  malesq#democrat |
             1 1  |  -.0271382   .0531186    -0.51   0.610    -.1314982    .0772219
                  |
       1.maleconc |   .3333333   .0665296     5.01   0.000     .2026251    .4640416
                  |
maleconc#democrat |
             1 1  |   .1041667   .0912809     1.14   0.254    -.0751695    .2835028
-----------------------------------------------------------------------------------
(est3 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1424668    .097319     1.46   0.144    -.0487323    .3336659
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1596282   .1030417     1.55   0.122    -.0428141    .3620706
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0171614   .1417342    -0.12   0.904    -.2956215    .2612986
------------------------------------------------------------------------------

. 
. ***Model 4: 7-Point DV, Attentive Sample
. eststo: reg disapproval1 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.malecon
> c 1.maleconc#democrat if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =        514
                                                F(8, 506)         =     323.06
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8423
                                                Root MSE          =     1.5226

-----------------------------------------------------------------------------------
                  |               Robust
     disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |   2.569444   .1425162    18.03   0.000     2.289448    2.849441
                  |
   femsq#democrat |
             1 1  |  -.2002137    .201942    -0.99   0.322    -.5969618    .1965344
                  |
        1.femconc |        4.2    .188391    22.29   0.000     3.829875    4.570125
                  |
 femconc#democrat |
             1 1  |   .4197183   .2905238     1.44   0.149    -.1510632    .9904998
                  |
         1.malesq |   2.666667   .1942339    13.73   0.000     2.285062    3.048271
                  |
  malesq#democrat |
             1 1  |  -.1041667   .2499297    -0.42   0.677    -.5951945    .3868611
                  |
       1.maleconc |   3.901961   .2408317    16.20   0.000     3.428808    4.375114
                  |
maleconc#democrat |
             1 1  |   .1917892   .3285674     0.58   0.560    -.4537351    .8373135
-----------------------------------------------------------------------------------
(est4 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7192375   .3795752     1.89   0.059    -.0264999    1.464975
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3952614    .389267     1.02   0.310    -.3695171     1.16004
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3239761   .5436967     0.60   0.552    -.7442048    1.392157
------------------------------------------------------------------------------

. 
. 
. ********************************************************************************
. *                                        TABLE A-9: STUDY 1 OTHER HETEROGENEITY                            *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Sexists and Women Leaders
. 
. eststo: regress disapproval1 i.female##c.hostsexism conciliatory democrat benevsexism secordersexism hawkish female
> _respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =        813
                                                F(16, 796)        =      11.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1971
                                                Root MSE          =     1.5056

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
               1.female |  -.2933972    .374759    -0.78   0.434     -1.02903    .4422354
             hostsexism |    .047973   .0923649     0.52   0.604    -.1333345    .2292805
                        |
    female#c.hostsexism |
                     1  |   .1269847   .1192051     1.07   0.287    -.1070087    .3609782
                        |
           conciliatory |   1.327296   .1065292    12.46   0.000     1.118184    1.536407
               democrat |  -.0055603   .1062852    -0.05   0.958    -.2141927     .203072
            benevsexism |   -.071508   .0567196    -1.26   0.208    -.1828456    .0398296
         secordersexism |   .0989639    .058121     1.70   0.089    -.0151247    .2130524
                hawkish |   .0574671   .0734496     0.78   0.434    -.0867106    .2016449
      female_respondent |   .0411889   .1082437     0.38   0.704     -.171288    .2536658
political_identfication |   .0954134   .0309861     3.08   0.002     .0345893    .1562375
              education |  -.0272652   .0271237    -1.01   0.315    -.0805077    .0259774
                    hhi |   .0000694   .0000819     0.85   0.397    -.0000914    .0002301
                    age |   .0020705   .0032168     0.64   0.520    -.0042439    .0083848
                  white |   .0514959   .1274523     0.40   0.686    -.1986864    .3016782
            SexismOrder |  -.0700456     .10788    -0.65   0.516    -.2818084    .1417173
       nonwhite_placebo |   .0133996   .1327871     0.10   0.920    -.2472547    .2740539
                  _cons |    1.80691   .4615891     3.91   0.000     .9008344    2.712986
-----------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. ***Model 2: Hawks and Conciliation
. 
. eststo: regress disapproval1 i.conciliatory##c.hawkish female democrat hostsexism benevsexism secordersexism female
> _respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =        813
                                                F(16, 796)        =      18.18
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2910
                                                Root MSE          =     1.4148

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
         1.conciliatory |  -2.353865   .4033574    -5.84   0.000    -3.145635   -1.562095
                hawkish |  -.5427955   .0924535    -5.87   0.000     -.724277    -.361314
                        |
 conciliatory#c.hawkish |
                     1  |   1.153116   .1240311     9.30   0.000     .9096492    1.396583
                        |
                 female |   .1224502    .101537     1.21   0.228    -.0768618    .3217622
               democrat |   .0205673    .100405     0.20   0.838    -.1765226    .2176571
             hostsexism |   .0646431    .064185     1.01   0.314    -.0613487     .190635
            benevsexism |  -.0598921   .0520436    -1.15   0.250     -.162051    .0422669
         secordersexism |   .0688258   .0539851     1.27   0.203    -.0371441    .1747957
      female_respondent |   .0095081   .1025593     0.09   0.926    -.1918106    .2108269
political_identfication |   .1028218    .029932     3.44   0.001     .0440668    .1615768
              education |  -.0018621   .0267346    -0.07   0.944    -.0543408    .0506166
                    hhi |   .0000647   .0000746     0.87   0.386    -.0000818    .0002112
                    age |   .0021292   .0031019     0.69   0.493    -.0039597     .008218
                  white |  -.0265968   .1218134    -0.22   0.827    -.2657102    .2125166
            SexismOrder |  -.1217994   .1007551    -1.21   0.227    -.3195764    .0759776
       nonwhite_placebo |  -.0107633   .1210241    -0.09   0.929    -.2483273    .2268007
                  _cons |   3.690631   .4458544     8.28   0.000     2.815442     4.56582
-----------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. ***Model 3: Republicans and Conciliation
. 
. eststo: regress disapproval1 i.conciliatory##c.political_identfication female democrat hostsexism benevsexism secor
> dersexism hawkish female_respondent education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =        813
                                                F(16, 796)        =      13.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2366
                                                Root MSE          =     1.4681

--------------------------------------------------------------------------------------------------------
                                       |               Robust
                          disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------------+----------------------------------------------------------------
                        1.conciliatory |   .1218385   .2185035     0.56   0.577    -.3070726    .5507496
               political_identfication |  -.0609064   .0381926    -1.59   0.111    -.1358766    .0140638
                                       |
conciliatory#c.political_identfication |
                                    1  |    .324711   .0536149     6.06   0.000     .2194677    .4299543
                                       |
                                female |   .1182012   .1061939     1.11   0.266    -.0902521    .3266544
                              democrat |   .0189232   .1040851     0.18   0.856    -.1853905     .223237
                            hostsexism |    .095097   .0640413     1.48   0.138    -.0306128    .2208068
                           benevsexism |   -.094962   .0554267    -1.71   0.087    -.2037619    .0138378
                        secordersexism |   .0939799   .0573044     1.64   0.101    -.0185056    .2064654
                               hawkish |   .0390352   .0719743     0.54   0.588    -.1022466    .1803171
                     female_respondent |   .0319312    .106058     0.30   0.763    -.1762553    .2401176
                             education |  -.0282005    .026371    -1.07   0.285    -.0799654    .0235644
                                   hhi |   .0000483   .0000799     0.60   0.546    -.0001087    .0002052
                                   age |    .002355   .0031046     0.76   0.448    -.0037393    .0084492
                                 white |   .0272464   .1258378     0.22   0.829    -.2197667    .2742595
                           SexismOrder |  -.0844003   .1047961    -0.81   0.421    -.2901097    .1213091
                      nonwhite_placebo |  -.0112747   .1282399    -0.09   0.930    -.2630032    .2404537
                                 _cons |   2.392447   .4342644     5.51   0.000     1.540009    3.244886
--------------------------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. ***Model 4: Women and Women Leaders
. 
. eststo: regress disapproval1 i.female##i.female_respondent conciliatory democrat hostsexism benevsexism secordersex
> ism hawkish political_identfication education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =        813
                                                F(16, 796)        =      11.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1957
                                                Root MSE          =     1.5069

------------------------------------------------------------------------------------------
                         |               Robust
            disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
                1.female |   .0570746   .1553216     0.37   0.713    -.2478136    .3619629
     1.female_respondent |  -.0037509   .1563877    -0.02   0.981     -.310732    .3032302
                         |
female#female_respondent |
                    1 1  |   .0767181   .2139994     0.36   0.720    -.3433518     .496788
                         |
            conciliatory |    1.32474   .1067294    12.41   0.000     1.115236    1.534245
                democrat |  -.0049281    .106474    -0.05   0.963    -.2139312     .204075
              hostsexism |     .11441   .0666841     1.72   0.087    -.0164875    .2453075
             benevsexism |  -.0744592   .0565763    -1.32   0.189    -.1855156    .0365971
          secordersexism |   .0973144   .0577564     1.68   0.092    -.0160583    .2106872
                 hawkish |   .0528785     .07341     0.72   0.472    -.0912215    .1969784
 political_identfication |   .0938856   .0311532     3.01   0.003     .0327335    .1550377
               education |  -.0283349   .0271901    -1.04   0.298    -.0817077    .0250379
                     hhi |   .0000702    .000081     0.87   0.387    -.0000889    .0002293
                     age |   .0023349   .0032262     0.72   0.469    -.0039979    .0086678
                   white |   .0469818   .1273913     0.37   0.712    -.2030808    .2970444
             SexismOrder |  -.0609374   .1084712    -0.56   0.574    -.2738607     .151986
        nonwhite_placebo |   .0074755   .1324621     0.06   0.955    -.2525409    .2674918
                   _cons |   1.654992   .4288193     3.86   0.000     .8132418    2.496743
------------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. clear 

. 
. 
. ********************************************************************************
. ********************************************************************************
. ********************************** STUDY 2 *************************************
. ********************************************************************************
. ********************************************************************************
. 
. import delimited "${data}/study2_main.csv", clear
(225 vars, 2,829 obs)

. est drop _all

. 
. ********************************************************************************
. *                                                                CLEAN STUDY 2 DATA                                
>                         *
. ********************************************************************************
. 
. do "${code}/GenderPeace_Cleaning2.do"

. 
. **********CLEAN DATA FROM STUDY 1***************
. 
. ***Drop Respondents that Failed Attention Check (80% passed)
. keep if disposition1_4=="Neither agree nor disagree"
(603 observations deleted)

. 
. ***SexismOrder (1 = Pre-Treatment; 0 = Post-Treatment)
. gen SexismOrder = 0

. replace SexismOrder = 1 if sexismorder==1
(1,051 real changes made)

. drop sexismorder

.  
. ***Hostile Sexism (1 = Least Sexist; 6 = Most Sexist)
. gen hostsexism1 = .
(2,226 missing values generated)

. replace hostsexism1 = 1 if sexism1_before1_1=="Strongly agree" | sexismpost11_1=="Strongly agree"
(450 real changes made)

. replace hostsexism1 = 2 if sexism1_before1_1=="Agree" | sexismpost11_1=="Agree"
(504 real changes made)

. replace hostsexism1 = 3 if sexism1_before1_1=="Somewhat agree" | sexismpost11_1=="Somewhat agree"
(598 real changes made)

. replace hostsexism1 = 4 if sexism1_before1_1=="Somewhat disagree" | sexismpost11_1=="Somewhat disagree"
(255 real changes made)

. replace hostsexism1 = 5 if sexism1_before1_1=="Disagree" | sexismpost11_1=="Disagree"
(162 real changes made)

. replace hostsexism1 = 6 if sexism1_before1_1=="Strongly disagree" | sexismpost11_1=="Strongly disagree"
(119 real changes made)

. 
. gen hostsexism2 = .
(2,226 missing values generated)

. replace hostsexism2 = 1 if sexism1_before1_2=="Strongly agree" | sexismpost11_2=="Strongly agree"
(278 real changes made)

. replace hostsexism2 = 2 if sexism1_before1_2=="Agree" | sexismpost11_2=="Agree"
(365 real changes made)

. replace hostsexism2 = 3 if sexism1_before1_2=="Somewhat agree" | sexismpost11_2=="Somewhat agree"
(586 real changes made)

. replace hostsexism2 = 4 if sexism1_before1_2=="Somewhat disagree" | sexismpost11_2=="Somewhat disagree"
(419 real changes made)

. replace hostsexism2 = 5 if sexism1_before1_2=="Disagree" | sexismpost11_2=="Disagree"
(235 real changes made)

. replace hostsexism2 = 6 if sexism1_before1_2=="Strongly disagree" | sexismpost11_2=="Strongly disagree"
(205 real changes made)

. 
. gen hostsexism3 = .
(2,226 missing values generated)

. replace hostsexism3 = 6 if sexism1_before1_3=="Strongly agree" | sexismpost11_3=="Strongly agree"
(162 real changes made)

. replace hostsexism3 = 5 if sexism1_before1_3=="Agree" | sexismpost11_3=="Agree"
(224 real changes made)

. replace hostsexism3 = 4 if sexism1_before1_3=="Somewhat agree" | sexismpost11_3=="Somewhat agree"
(432 real changes made)

. replace hostsexism3 = 3 if sexism1_before1_3=="Somewhat disagree" | sexismpost11_3=="Somewhat disagree"
(457 real changes made)

. replace hostsexism3 = 2 if sexism1_before1_3=="Disagree" | sexismpost11_3=="Disagree"
(404 real changes made)

. replace hostsexism3 = 1 if sexism1_before1_3=="Strongly disagree" | sexismpost11_3=="Strongly disagree"
(409 real changes made)

. 
. gen hostsexism4 = .
(2,226 missing values generated)

. replace hostsexism4 = 6 if sexism1_before1_4=="Strongly agree" | sexismpost11_4=="Strongly agree"
(152 real changes made)

. replace hostsexism4 = 5 if sexism1_before1_4=="Agree" | sexismpost11_4=="Agree"
(187 real changes made)

. replace hostsexism4 = 4 if sexism1_before1_4=="Somewhat agree" | sexismpost11_4=="Somewhat agree"
(343 real changes made)

. replace hostsexism4 = 3 if sexism1_before1_4=="Somewhat disagree" | sexismpost11_4=="Somewhat disagree"
(431 real changes made)

. replace hostsexism4 = 2 if sexism1_before1_4=="Disagree" | sexismpost11_4=="Disagree"
(435 real changes made)

. replace hostsexism4 = 1 if sexism1_before1_4=="Strongly disagree" | sexismpost11_4=="Strongly disagree"
(540 real changes made)

. 
. gen hostsexism = (hostsexism1 + hostsexism2 + hostsexism3 + hostsexism4) / 4
(138 missing values generated)

. 
. summarize hostsexism, detail 

                         hostsexism
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%         1.25              1
10%          1.5              1       Obs               2,088
25%         2.25              1       Sum of Wgt.       2,088

50%         3.25                      Mean           2.990062
                        Largest       Std. Dev.      .9961248
75%          3.5              6
90%            4              6       Variance       .9922646
95%          4.5              6       Skewness      -.0868825
99%          5.5              6       Kurtosis       2.940402

. 
. gen hostsexismIQR = .
(2,226 missing values generated)

. replace hostsexismIQR = 0 if hostsexism<=2.25
(549 real changes made)

. replace hostsexismIQR = 1 if hostsexism>=3.5
(988 real changes made)

. replace hostsexismIQR = . if hostsexism==.
(138 real changes made, 138 to missing)

. 
. 
. ***Benevolent Sexism (1 = Least Sexist; 6 = Most Sexist)
. *Note: Questions 3 and 4 are negatively correlated with 1 and 2
. gen benevsexism1 = .
(2,226 missing values generated)

. replace benevsexism1= 6 if sexism1_before1_5=="Strongly agree" | sexismpost11_5=="Strongly agree"
(189 real changes made)

. replace benevsexism1= 5 if sexism1_before1_5=="Agree" | sexismpost11_5=="Agree"
(313 real changes made)

. replace benevsexism1 = 4 if sexism1_before1_5=="Somewhat agree" | sexismpost11_5=="Somewhat agree"
(596 real changes made)

. replace benevsexism1 = 3 if sexism1_before1_5=="Somewhat disagree" | sexismpost11_5=="Somewhat disagree"
(477 real changes made)

. replace benevsexism1 = 2 if sexism1_before1_5=="Disagree" | sexismpost11_5=="Disagree"
(326 real changes made)

. replace benevsexism1 = 1 if sexism1_before1_5=="Strongly disagree" | sexismpost11_5=="Strongly disagree"
(187 real changes made)

. 
. gen benevsexism2 = .
(2,226 missing values generated)

. replace benevsexism2= 6 if sexism2_before1_1=="Strongly agree" | sexismpost21_1=="Strongly agree"
(170 real changes made)

. replace benevsexism2= 5 if sexism2_before1_1=="Agree" | sexismpost21_1=="Agree"
(311 real changes made)

. replace benevsexism2 = 4 if sexism2_before1_1=="Somewhat agree" | sexismpost21_1=="Somewhat agree"
(651 real changes made)

. replace benevsexism2 = 3 if sexism2_before1_1=="Somewhat disagree" | sexismpost21_1=="Somewhat disagree"
(515 real changes made)

. replace benevsexism2 = 2 if sexism2_before1_1=="Disagree" | sexismpost21_1=="Disagree"
(262 real changes made)

. replace benevsexism2 = 1 if sexism2_before1_1=="Strongly disagree" | sexismpost21_1=="Strongly disagree"
(179 real changes made)

. 
. gen benevsexism3 = .
(2,226 missing values generated)

. replace benevsexism3= 1 if sexism2_before1_2=="Strongly agree" | sexismpost21_2=="Strongly agree"
(182 real changes made)

. replace benevsexism3= 2 if sexism2_before1_2=="Agree" | sexismpost21_2=="Agree"
(252 real changes made)

. replace benevsexism3 = 3 if sexism2_before1_2=="Somewhat agree" | sexismpost21_2=="Somewhat agree"
(440 real changes made)

. replace benevsexism3 = 4 if sexism2_before1_2=="Somewhat disagree" | sexismpost21_2=="Somewhat disagree"
(555 real changes made)

. replace benevsexism3 = 5 if sexism2_before1_2=="Disagree" | sexismpost21_2=="Disagree"
(350 real changes made)

. replace benevsexism3 = 6 if sexism2_before1_2=="Strongly disagree" | sexismpost21_2=="Strongly disagree"
(309 real changes made)

. 
. gen benevsexism4 = .
(2,226 missing values generated)

. replace benevsexism4= 1 if sexism2_before1_3=="Strongly agree" | sexismpost21_3=="Strongly agree"
(110 real changes made)

. replace benevsexism4= 2 if sexism2_before1_3=="Agree" | sexismpost21_3=="Agree"
(146 real changes made)

. replace benevsexism4 = 3 if sexism2_before1_3=="Somewhat agree" | sexismpost21_3=="Somewhat agree"
(273 real changes made)

. replace benevsexism4 = 4 if sexism2_before1_3=="Somewhat disagree" | sexismpost21_3=="Somewhat disagree"
(498 real changes made)

. replace benevsexism4 = 5 if sexism2_before1_3=="Disagree" | sexismpost21_3=="Disagree"
(431 real changes made)

. replace benevsexism4 = 6 if sexism2_before1_3=="Strongly disagree" | sexismpost21_3=="Strongly disagree"
(630 real changes made)

. 
. *Since items 3 and 4 are negatively correlated with 1 and 2 going to drop the latter two from the index. Yields a g
> reater reliability measure than reverse coding 3 and 4
. gen benevsexism = (benevsexism1 + benevsexism2) / 2
(138 missing values generated)

. 
. summarize benevsexism, detail

                         benevsexism
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%          1.5              1
10%            2              1       Obs               2,088
25%            3              1       Sum of Wgt.       2,088

50%          3.5                      Mean           3.539272
                        Largest       Std. Dev.        1.1959
75%          4.5              6
90%            5              6       Variance       1.430177
95%          5.5              6       Skewness      -.0367175
99%            6              6       Kurtosis       2.617634

. 
. 
. gen benevsexismIQR = .
(2,226 missing values generated)

. replace benevsexismIQR = 0 if benevsexism<=3
(839 real changes made)

. replace benevsexismIQR = 1 if benevsexism>=4.5
(676 real changes made)

. replace benevsexismIQR = . if benevsexism==.
(138 real changes made, 138 to missing)

. 
. 
. ***Second Order Sexism (1 = Least Sexist; 6 = Most Sexist)
. gen secordersexism_amer_citz = .
(2,226 missing values generated)

. replace secordersexism_amer_citz = 6 if sexism2_before1_4=="Strongly agree" | sexismpost21_4=="Strongly agree"
(232 real changes made)

. replace secordersexism_amer_citz = 5 if sexism2_before1_4=="Agree" | sexismpost21_4=="Agree"
(373 real changes made)

. replace secordersexism_amer_citz = 4 if sexism2_before1_4=="Somewhat agree" | sexismpost21_4=="Somewhat agree"
(838 real changes made)

. replace secordersexism_amer_citz = 3 if sexism2_before1_4=="Somewhat disagree" | sexismpost21_4=="Somewhat disagree
> "
(371 real changes made)

. replace secordersexism_amer_citz = 2 if sexism2_before1_4=="Disagree" | sexismpost21_4=="Disagree"
(162 real changes made)

. replace secordersexism_amer_citz = 1 if sexism2_before1_4=="Strongly disagree" | sexismpost21_4=="Strongly disagree
> "
(112 real changes made)

. 
. gen secordersexism_for_lead = .
(2,226 missing values generated)

. replace secordersexism_for_lead = 6 if sexism2_before1_5=="Strongly agree" | sexismpost21_5=="Strongly agree"
(242 real changes made)

. replace secordersexism_for_lead = 5 if sexism2_before1_5=="Agree" | sexismpost21_5=="Agree"
(368 real changes made)

. replace secordersexism_for_lead = 4 if sexism2_before1_5=="Somewhat agree" | sexismpost21_5=="Somewhat agree"
(756 real changes made)

. replace secordersexism_for_lead = 3 if sexism2_before1_5=="Somewhat disagree" | sexismpost21_5=="Somewhat disagree"
(445 real changes made)

. replace secordersexism_for_lead = 2 if sexism2_before1_5=="Disagree" | sexismpost21_5=="Disagree"
(168 real changes made)

. replace secordersexism_for_lead = 1 if sexism2_before1_5=="Strongly disagree" | sexismpost21_5=="Strongly disagree"
(109 real changes made)

. 
. gen secordersexism = (secordersexism_amer_citz + secordersexism_for_lead) / 2 
(138 missing values generated)

. 
. gen secordersexismIQR = .
(2,226 missing values generated)

. replace secordersexismIQR = 0 if secordersexism<=3
(534 real changes made)

. replace secordersexismIQR = 1 if secordersexism>=4.5
(860 real changes made)

. replace secordersexismIQR = . if secordersexism==.
(138 real changes made, 138 to missing)

. 
. 
. ***Militant Assertiveness (1 = Least Hawkish; 6 = Most Hawkish)
. gen hawkish1 = .
(2,226 missing values generated)

. replace hawkish1 = 5 if disposition1_1=="Strongly agree" 
(301 real changes made)

. replace hawkish1 = 4 if disposition1_1=="Somewhat agree" 
(533 real changes made)

. replace hawkish1 = 3 if disposition1_1=="Neither agree nor disagree" 
(609 real changes made)

. replace hawkish1 = 2 if disposition1_1=="Somewhat disagree" 
(443 real changes made)

. replace hawkish1 = 1 if disposition1_1=="Strongly disagree"
(337 real changes made)

. 
. gen hawkish2 = .
(2,226 missing values generated)

. replace hawkish2 = 5 if disposition1_2=="Strongly agree" 
(350 real changes made)

. replace hawkish2 = 4 if disposition1_2=="Somewhat agree" 
(919 real changes made)

. replace hawkish2 = 3 if disposition1_2=="Neither agree nor disagree" 
(483 real changes made)

. replace hawkish2 = 2 if disposition1_2=="Somewhat disagree" 
(294 real changes made)

. replace hawkish2 = 1 if disposition1_2=="Strongly disagree"
(176 real changes made)

. 
. gen hawkish3 = .
(2,226 missing values generated)

. replace hawkish3 = 1 if disposition1_3=="Strongly agree" 
(260 real changes made)

. replace hawkish3 = 2 if disposition1_3=="Somewhat agree" 
(583 real changes made)

. replace hawkish3 = 3 if disposition1_3=="Neither agree nor disagree" 
(646 real changes made)

. replace hawkish3 = 4 if disposition1_3=="Somewhat disagree" 
(473 real changes made)

. replace hawkish3 = 5 if disposition1_3=="Strongly disagree"
(260 real changes made)

. 
. gen hawkish = (hawkish1 + hawkish2 + hawkish3) / 3
(7 missing values generated)

. 
. summarize hawkish, detail 

                           hawkish
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%     1.333333              1
10%            2              1       Obs               2,219
25%     2.666667              1       Sum of Wgt.       2,219

50%            3                      Mean           3.131891
                        Largest       Std. Dev.        .87119
75%     3.666667              5
90%     4.333333              5       Variance        .758972
95%     4.666667              5       Skewness      -.2350583
99%            5              5       Kurtosis       2.955047

. 
. gen hawkishIQR = .
(2,226 missing values generated)

. replace hawkishIQR = 0 if hawkish<=2.7
(721 real changes made)

. replace hawkishIQR = 1 if hawkish>=3.6
(761 real changes made)

. replace hawkishIQR = . if hawkish==.
(7 real changes made, 7 to missing)

. 
. 
. *Political ID (1 = Most Democrat; 6 = Most Republican)
. gen political_identfication = 1

. replace political_identfication = 2 if political_party==2
(298 real changes made)

. replace political_identfication = 3 if political_party==3 | political_party==6
(174 real changes made)

. replace political_identfication = 4 if political_party==4 | political_party==7
(315 real changes made)

. replace political_identfication = 5 if political_party==8 | political_party==5
(157 real changes made)

. replace political_identfication = 6 if political_party==9
(231 real changes made)

. replace political_identfication = 7 if political_party==10
(504 real changes made)

. 
. gen democratic_respondent = 0

. replace democratic_respondent = 1 if political_identfication<=3
(1,019 real changes made)

. 
. gen republican_respondent = 0

. replace republican_respondent = 1 if political_identfication>=5
(892 real changes made)

. 
. ***Code Education (1 = Least; 8 = Most; Drop Missing)
. replace education = . if education==-3105 | education==-10
(11 real changes made, 11 to missing)

. 
. summarize education, detail

                          education
-------------------------------------------------------------
      Percentiles      Smallest
 1%            1              1
 5%            2              1
10%            2              1       Obs               2,214
25%            3              1       Sum of Wgt.       2,214

50%            5                      Mean           4.633695
                        Largest       Std. Dev.      1.954513
75%            6              8
90%            7              8       Variance        3.82012
95%            7              8       Skewness       -.195285
99%            8             10       Kurtosis       1.828174

. 
. gen educationIQR = .
(2,226 missing values generated)

. replace educationIQR = 0 if education<=3
(621 real changes made)

. replace educationIQR = 1 if education>=6
(973 real changes made)

. replace educationIQR = . if education==.
(12 real changes made, 12 to missing)

. 
. 
. ***Code Binary Ethnicity Variables
. gen white = 0

. replace white = 1 if ethnicity==1
(1,622 real changes made)

. 
. gen black = 0

. replace black = 1 if ethnicity==2
(262 real changes made)

. 
. gen ethnicity_other = 0

. replace ethnicity_other = 1 if white==0 & black==0
(342 real changes made)

. 
. 
. ***Code Female Respondent Dummy
. gen female_respondent = 0

. replace female_respondent = 1 if gender==2
(1,172 real changes made)

. 
. 
. ***Code Income (1 = Least; 24 = Most; Drop Missing)
. gen income = hhi
(1 missing value generated)

. replace income = . if hhi==-3105
(119 real changes made, 119 to missing)

. 
. 
. ***Code Binary Hispanic Variable 
. gen hispanic_binary = 1

. replace hispanic_binary = 0 if hispanic==1 | hispanic==15  | hispanic==16 
(1,973 real changes made)

. 
. 
. ***Code Binary South Variable
. gen south = 0

. replace south = 1 if region==3
(852 real changes made)

. 
. 
. ***Code Treatment Variables 
. rename male male_name

. rename female female_name

. 
. gen female = 0

. replace female = 1 if cond9_dv!="" | cond10_dv!="" | cond11_dv!="" | cond12_dv!="" | cond13_dv!="" | cond14_dv!="" 
> | cond15_dv!="" | cond16_dv!="" 
(1,083 real changes made)

. 
. gen male = 0

. replace male = 1 if cond1_dv!="" | cond2_dv!="" | cond3_dv!="" | cond4_dv!="" | cond5_dv!="" | cond6_dv!="" | cond7
> _dv!="" | cond8_dv!="" 
(1,058 real changes made)

. 
. gen hawk = 0

. replace hawk = 1 if cond1_dv!="" | cond2_dv!="" | cond5_dv!="" | cond6_dv!="" | cond9_dv!="" | cond10_dv!="" | cond
> 13_dv!="" | cond14_dv!="" 
(1,073 real changes made)

. 
. gen dove = 0

. replace dove = 1 if cond3_dv!="" | cond4_dv!="" | cond7_dv!="" | cond8_dv!="" | cond11_dv!="" | cond12_dv!="" | con
> d15_dv!="" | cond16_dv!="" 
(1,068 real changes made)

. 
. gen statusquo = 0

. replace statusquo = 1 if cond1_dv!="" | cond3_dv!="" | cond5_dv!="" | cond7_dv!="" | cond9_dv!="" | cond11_dv!="" |
>  cond13_dv!="" | cond15_dv!="" 
(1,069 real changes made)

. 
. gen conciliatory = 0

. replace conciliatory = 1 if cond2_dv!="" | cond4_dv!="" | cond6_dv!="" | cond8_dv!="" | cond10_dv!="" | cond12_dv!=
> "" | cond14_dv!="" | cond16_dv!="" 
(1,072 real changes made)

. 
. gen democrat = 0

. replace democrat = 1 if cond5_dv!="" | cond6_dv!="" | cond7_dv!="" | cond8_dv!="" | cond13_dv!="" | cond14_dv!="" |
>  cond15_dv!="" | cond16_dv!="" 
(1,070 real changes made)

. 
. gen republican = 0

. replace republican = 1 if cond1_dv!="" | cond2_dv!="" | cond3_dv!="" | cond4_dv!="" | cond9_dv!="" | cond10_dv!="" 
> | cond11_dv!="" | cond12_dv!="" 
(1,071 real changes made)

. 
. gen femsq = 0

. replace femsq = 1 if female==1 & statusquo==1
(543 real changes made)

. 
. gen malesq = 0

. replace malesq = 1 if male==1 & statusquo==1
(526 real changes made)

. 
. gen maleconc = 0

. replace maleconc= 1 if male==1 & conciliatory==1
(532 real changes made)

. 
. gen femconc = 0

. replace femconc= 1 if female==1 & conciliatory==1
(540 real changes made)

. 
. gen hawksq = 0

. replace hawksq = 1 if hawk==1 & statusquo==1
(536 real changes made)

. 
. gen dovesq = 0

. replace dovesq = 1 if dove==1 & statusquo==1
(533 real changes made)

. 
. gen hawkconc = 0

. replace hawkconc = 1 if hawk==1 & conciliatory==1
(537 real changes made)

. 
. gen doveconc = 0

. replace doveconc = 1 if dove==1 & conciliatory==1
(535 real changes made)

. 
. gen demsq = 0

. replace demsq = 1 if democrat==1 & statusquo==1
(529 real changes made)

. 
. gen repsq = 0

. replace repsq = 1 if republican==1 & statusquo==1
(540 real changes made)

. 
. gen demconc = 0

. replace demconc = 1 if democrat==1 & conciliatory==1
(541 real changes made)

. 
. gen repconc = 0

. replace repconc = 1 if republican==1 & conciliatory==1
(531 real changes made)

. 
. gen femsq_in = 0

. replace femsq_in = 1 if (femsq==1 & democratic_respondent==1 & democrat==1) | (femsq==1 & republican_respondent==1 
> & republican==1)
(233 real changes made)

. 
. gen femconc_in = 0

. replace femconc_in = 1 if (femconc==1 & democratic_respondent==1 & democrat==1) | (femconc==1 & republican_responde
> nt==1 & republican==1)
(232 real changes made)

. 
. gen malesq_in = 0

. replace malesq_in = 1 if (malesq==1 & democratic_respondent==1 & democrat==1) | (malesq==1 & republican_respondent=
> =1 & republican==1)
(224 real changes made)

. 
. gen maleconc_in = 0

. replace maleconc_in = 1 if (maleconc==1 & democratic_respondent==1 & democrat==1) | (maleconc==1 & republican_respo
> ndent==1 & republican==1)
(227 real changes made)

. 
. gen femsq_out = 0

. replace femsq_out = 1 if (femsq==1 & democratic_respondent==1 & republican==1) | (femsq==1 & republican_respondent=
> =1 & democrat==1)
(235 real changes made)

. 
. gen femconc_out = 0

. replace femconc_out = 1 if (femconc==1 & democratic_respondent==1 & republican==1) | (femconc==1 & republican_respo
> ndent==1 & democrat==1)
(233 real changes made)

. 
. gen malesq_out = 0

. replace malesq_out = 1 if (malesq==1 & democratic_respondent==1 & republican==1) | (malesq==1 & republican_responde
> nt==1 & democrat==1)
(227 real changes made)

. 
. gen maleconc_out = 0

. replace maleconc_out = 1 if (maleconc==1 & democratic_respondent==1 & republican==1) | (maleconc==1 & republican_re
> spondent==1 & democrat==1)
(228 real changes made)

. 
. gen dovesq_in = 0

. replace dovesq_in = 1 if (dovesq==1 & democratic_respondent==1 & democrat==1) | (dovesq==1 & republican_respondent=
> =1 & republican==1)
(229 real changes made)

. 
. gen doveconc_in = 0

. replace doveconc_in = 1 if (doveconc==1 & democratic_respondent==1 & democrat==1) | (doveconc==1 & republican_respo
> ndent==1 & republican==1)
(229 real changes made)

. 
. gen hawksq_in = 0

. replace hawksq_in = 1 if (hawksq==1 & democratic_respondent==1 & democrat==1) | (hawksq==1 & republican_respondent=
> =1 & republican==1)
(228 real changes made)

. 
. gen hawkconc_in = 0

. replace hawkconc_in = 1 if (hawkconc==1 & democratic_respondent==1 & democrat==1) | (hawkconc==1 & republican_respo
> ndent==1 & republican==1)
(230 real changes made)

. 
. gen dovesq_out = 0

. replace dovesq_out = 1 if (dovesq==1 & democratic_respondent==1 & republican==1) | (dovesq==1 & republican_responde
> nt==1 & democrat==1)
(229 real changes made)

. 
. gen doveconc_out = 0

. replace doveconc_out = 1 if (doveconc==1 & democratic_respondent==1 & republican==1) | (doveconc==1 & republican_re
> spondent==1 & democrat==1)
(232 real changes made)

. 
. gen hawksq_out = 0

. replace hawksq_out = 1 if (hawksq==1 & democratic_respondent==1 & republican==1) | (hawksq==1 & republican_responde
> nt==1 & democrat==1)
(233 real changes made)

. 
. gen hawkconc_out = 0

. replace hawkconc_out = 1 if (hawkconc==1 & democratic_respondent==1 & republican==1) | (hawkconc==1 & republican_re
> spondent==1 & democrat==1)
(229 real changes made)

. 
. gen in_partisan = 0

. replace in_partisan = 1 if (democratic_respondent==1 & democrat==1) | (republican_respondent==1 & republican==1)
(916 real changes made)

. 
. gen out_partisan = 0

. replace out_partisan = 1 if (democratic_respondent==1 & republican==1) | (republican_respondent==1 & democrat==1)
(923 real changes made)

. 
. 
. 
. ***Code Full Disapproval Variable 1 (1 = Strongly Approve; 7 = Strongly Disapprove)
. gen disapproval1 = .
(2,226 missing values generated)

. replace disapproval1 = 1 if cond1_dv=="Strongly approve" | cond2_dv=="Strongly approve" | cond3_dv=="Strongly appro
> ve" | cond4_dv=="Strongly approve" | cond5_dv=="Strongly approve" | cond6_dv=="Strongly approve" | cond7_dv=="Stron
> gly approve" | cond8_dv=="Strongly approve" | cond9_dv=="Strongly approve" | cond10_dv=="Strongly approve" | cond11
> _dv=="Strongly approve" | cond12_dv=="Strongly approve" | cond13_dv=="Strongly approve" | cond14_dv=="Strongly appr
> ove" | cond15_dv=="Strongly approve" | cond16_dv=="Strongly approve"  
(364 real changes made)

. replace disapproval1 = 2 if cond1_dv=="Approve" | cond2_dv=="Approve" | cond3_dv=="Approve" | cond4_dv=="Approve" |
>  cond5_dv=="Approve" | cond6_dv=="Approve" | cond7_dv=="Approve" | cond8_dv=="Approve" | cond9_dv=="Approve" | cond
> 10_dv=="Approve" | cond11_dv=="Approve" | cond12_dv=="Approve" | cond13_dv=="Approve" | cond14_dv=="Approve" | cond
> 15_dv=="Approve" | cond16_dv=="Approve"  
(472 real changes made)

. replace disapproval1 = 3 if cond1_dv=="Somewhat approve" | cond2_dv=="Somewhat approve" | cond3_dv=="Somewhat appro
> ve" | cond4_dv=="Somewhat approve" | cond5_dv=="Somewhat approve" | cond6_dv=="Somewhat approve" | cond7_dv=="Somew
> hat approve" | cond8_dv=="Somewhat approve" | cond9_dv=="Somewhat approve" | cond10_dv=="Somewhat approve" | cond11
> _dv=="Somewhat approve" | cond12_dv=="Somewhat approve" | cond13_dv=="Somewhat approve" | cond14_dv=="Somewhat appr
> ove" | cond15_dv=="Somewhat approve" | cond16_dv=="Somewhat approve"  
(495 real changes made)

. replace disapproval1 = 4 if cond1_dv=="Neither approve nor disapprove" | cond2_dv=="Neither approve nor disapprove"
>  | cond3_dv=="Neither approve nor disapprove" | cond4_dv=="Neither approve nor disapprove" | cond5_dv=="Neither app
> rove nor disapprove" | cond6_dv=="Neither approve nor disapprove" | cond7_dv=="Neither approve nor disapprove" | co
> nd8_dv=="Neither approve nor disapprove" | cond9_dv=="Neither approve nor disapprove" | cond10_dv=="Neither approve
>  nor disapprove" | cond11_dv=="Neither approve nor disapprove" | cond12_dv=="Neither approve nor disapprove" | cond
> 13_dv=="Neither approve nor disapprove" | cond14_dv=="Neither approve nor disapprove" | cond15_dv=="Neither approve
>  nor disapprove" | cond16_dv=="Neither approve nor disapprove"  
(378 real changes made)

. replace disapproval1 = 5 if cond1_dv=="Somewhat disapprove" | cond2_dv=="Somewhat disapprove" | cond3_dv=="Somewhat
>  disapprove" | cond4_dv=="Somewhat disapprove" | cond5_dv=="Somewhat disapprove" | cond6_dv=="Somewhat disapprove" 
> | cond7_dv=="Somewhat disapprove" | cond8_dv=="Somewhat disapprove" | cond9_dv=="Somewhat disapprove" | cond10_dv==
> "Somewhat disapprove" | cond11_dv=="Somewhat disapprove" | cond12_dv=="Somewhat disapprove" | cond13_dv=="Somewhat 
> disapprove" | cond14_dv=="Somewhat disapprove" | cond15_dv=="Somewhat disapprove" | cond16_dv=="Somewhat disapprove
> "  
(238 real changes made)

. replace disapproval1 = 6 if cond1_dv=="Disapprove" | cond2_dv=="Disapproving" | cond3_dv=="Disapprove" | cond4_dv==
> "Disapprove" | cond5_dv=="Disapprove" | cond6_dv=="Disapprove" | cond7_dv=="Disapprove" | cond8_dv=="Disapprove" | 
> cond9_dv=="Disapprove" | cond10_dv=="Disapprove" | cond11_dv=="Disapprove" | cond12_dv=="Disapprove" | cond13_dv=="
> Disapproving" | cond14_dv=="Disapprove" | cond15_dv=="Disapprove" | cond16_dv=="Disapprove"  
(107 real changes made)

. replace disapproval1 = 7 if cond1_dv=="Strongly disapprove" | cond2_dv=="Strongly disapprove" | cond3_dv=="Strongly
>  disapprove" | cond4_dv=="Strongly disapprove" | cond5_dv=="Strongly disapprove" | cond6_dv=="Strongly disapprove" 
> | cond7_dv=="Strongly disapprove" | cond8_dv=="Strongly disapprove" | cond9_dv=="Strongly disapprove" | cond10_dv==
> "Strongly disapprove" | cond11_dv=="Strongly disapprove" | cond12_dv=="Strongly disapprove" | cond13_dv=="Strongly 
> disapprove" | cond14_dv=="Strongly disapprove" | cond15_dv=="Strongly disapprove" | cond16_dv=="Strongly disapprove
> "  
(87 real changes made)

. 
. 
. ***Code Binart Disapproval Variable 1 (1 = Disapprove; 0 = Don't Disapprove)
. gen disapproval1_binary = 0

. replace disapproval1_binary = 1 if disapproval1>=5
(517 real changes made)

. replace disapproval1_binary = . if disapproval1==.
(85 real changes made, 85 to missing)

. 
. 
. ***Code Full Disapproval Variable 2 (1 = Strongly Approve; 7 = Strongly Disapprove)
. gen disapproval2 = .
(2,226 missing values generated)

. replace disapproval2 = 1 if cond1_outcome_dv=="Strongly approve" | cond2_outcome_dv=="Strongly approve" | cond3_out
> come_dv=="Strongly approve" | cond4_outcome_dv=="Strongly approve" | cond5_outcome_dv=="Strongly approve" | cond6_o
> utcome_dv=="Strongly approve" | cond7_outcome_dv=="Strongly approve" | cond8_outcome_dv=="Strongly approve" | cond9
> _outcome_dv=="Strongly approve" | cond10_outcome_dv=="Strongly approve" | cond11_outcome_dv=="Strongly approve" | c
> ond12_outcome_dv=="Strongly approve" | cond13_outcome_dv=="Strongly approve" | cond14_outcome_dv=="Strongly approve
> " | cond15_outcome_dv=="Strongly approve" | cond16_outcome_dv=="Strongly approve"  
(634 real changes made)

. replace disapproval2 = 2 if cond1_outcome_dv=="Approve" | cond2_outcome_dv=="Approve" | cond3_outcome_dv=="Approve"
>  | cond4_outcome_dv=="Approve" | cond5_outcome_dv=="Approve" | cond6_outcome_dv=="Approve" | cond7_outcome_dv=="App
> rove" | cond8_outcome_dv=="Approve" | cond9_outcome_dv=="Approve" | cond10_outcome_dv=="Approve" | cond11_outcome_d
> v=="Approve" | cond12_outcome_dv=="Approve" | cond13_outcome_dv=="Approve" | cond14_outcome_dv=="Approve" | cond15_
> outcome_dv=="Approve" | cond16_outcome_dv=="Approve"  
(573 real changes made)

. replace disapproval2 = 3 if cond1_outcome_dv=="Somewhat approve" | cond2_outcome_dv=="Somewhat approve" | cond3_out
> come_dv=="Somewhat approve" | cond4_outcome_dv=="Somewhat approve" | cond5_outcome_dv=="Somewhat approve" | cond6_o
> utcome_dv=="Somewhat approve" | cond7_outcome_dv=="Somewhat approve" | cond8_outcome_dv=="Somewhat approve" | cond9
> _outcome_dv=="Somewhat approve" | cond10_outcome_dv=="Somewhat approve" | cond11_outcome_dv=="Somewhat approve" | c
> ond12_outcome_dv=="Somewhat approve" | cond13_outcome_dv=="Somewhat approve" | cond14_outcome_dv=="Somewhat approve
> " | cond15_outcome_dv=="Somewhat approve" | cond16_outcome_dv=="Somewhat approve"  
(359 real changes made)

. replace disapproval2 = 4 if cond1_outcome_dv=="Neither approve nor disapprove" | cond2_outcome_dv=="Neither approve
>  nor disapprove" | cond3_outcome_dv=="Neither approve nor disapprove" | cond4_outcome_dv=="Neither approve nor disa
> pprove" | cond5_outcome_dv=="Neither approve nor disapprove" | cond6_outcome_dv=="Neither approve nor disapprove" |
>  cond7_outcome_dv=="Neither approve nor disapprove" | cond8_outcome_dv=="Neither approve nor disapprove" | cond9_ou
> tcome_dv=="Neither approve nor disapprove" | cond10_outcome_dv=="Neither approve nor disapprove" | cond11_outcome_d
> v=="Neither approve nor disapprove" | cond12_outcome_dv=="Neither approve nor disapprove" | cond13_outcome_dv=="Nei
> ther approve nor disapprove" | cond14_outcome_dv=="Neither approve nor disapprove" | cond15_outcome_dv=="Neither ap
> prove nor disapprove" | cond16_outcome_dv=="Neither approve nor disapprove"  
(297 real changes made)

. replace disapproval2 = 5 if cond1_outcome_dv=="Somewhat disapprove" | cond2_outcome_dv=="Somewhat disapprove" | con
> d3_outcome_dv=="Somewhat disapprove" | cond4_outcome_dv=="Somewhat disapprove" | cond5_outcome_dv=="Somewhat disapp
> rove" | cond6_outcome_dv=="Somewhat disapprove" | cond7_outcome_dv=="Somewhat disapprove" | cond8_outcome_dv=="Some
> what disapprove" | cond9_outcome_dv=="Somewhat disapprove" | cond10_outcome_dv=="Somewhat disapprove" | cond11_outc
> ome_dv=="Somewhat disapprove" | cond12_outcome_dv=="Somewhat disapprove" | cond13_outcome_dv=="Somewhat disapprove"
>  | cond14_outcome_dv=="Somewhat disapprove" | cond15_outcome_dv=="Somewhat disapprove" | cond16_outcome_dv=="Somewh
> at disapprove"  
(59 real changes made)

. replace disapproval2 = 6 if cond1_outcome_dv=="Disapprove" | cond2_outcome_dv=="Disapprove" | cond3_outcome_dv=="Di
> sapprove" | cond4_outcome_dv=="Disapprove" | cond5_outcome_dv=="Disapprove" | cond6_outcome_dv=="Disapprove" | cond
> 7_outcome_dv=="Disapprove" | cond8_outcome_dv=="Disapprove" | cond9_outcome_dv=="Disapprove" | cond10_outcome_dv=="
> Disapprove" | cond11_outcome_dv=="Disapprove" | cond12_outcome_dv=="Disapprove" | cond13_outcome_dv=="Disapprove" |
>  cond14_outcome_dv=="Disapprove" | cond15_outcome_dv=="Disapprove" | cond16_outcome_dv=="Disapprove"  
(44 real changes made)

. replace disapproval2 = 7 if cond1_outcome_dv=="Strongly disapprove" | cond2_outcome_dv=="Strongly disapprove" | con
> d3_outcome_dv=="Strongly disapprove" | cond4_outcome_dv=="Strongly disapprove" | cond5_outcome_dv=="Strongly disapp
> rove" | cond6_outcome_dv=="Strongly disapprove" | cond7_outcome_dv=="Strongly disapprove" | cond8_outcome_dv=="Stro
> ngly disapprove" | cond9_outcome_dv=="Strongly disapprove" | cond10_outcome_dv=="Strongly disapprove" | cond11_outc
> ome_dv=="Strongly disapprove" | cond12_outcome_dv=="Strongly disapprove" | cond13_outcome_dv=="Strongly disapprove"
>  | cond14_outcome_dv=="Strongly disapprove" | cond15_outcome_dv=="Strongly disapprove" | cond16_outcome_dv=="Strong
> ly disapprove"  
(39 real changes made)

. 
. 
. ***Code Binart Disapproval Variable 2 (1 = Disapprove; 0 = Don't Disapprove)
. gen disapproval2_binary = 0

. replace disapproval2_binary = 1 if disapproval2>=5
(363 real changes made)

. replace disapproval2_binary = . if disapproval2==.
(221 real changes made, 221 to missing)

. 
. 
. ***Code Mechanisms 
. 
. *Best Strategy
. gen beststrategy1 = .
(2,226 missing values generated)

. replace beststrategy1 = 7 if strategy1=="Strongly agree" 
(313 real changes made)

. replace beststrategy1 = 6 if strategy1=="Agree" 
(449 real changes made)

. replace beststrategy1 = 5 if strategy1=="Somewhat agree"
(433 real changes made)

. replace beststrategy1 = 4 if strategy1=="Neither agree nor disagree"
(405 real changes made)

. replace beststrategy1 = 3 if strategy1=="Somewhat disagree" 
(194 real changes made)

. replace beststrategy1 = 2 if strategy1=="Disagree" 
(107 real changes made)

. replace beststrategy1 = 1 if strategy1=="Strongly disagree" 
(119 real changes made)

. 
. gen beststrategy1_binary = 0

. replace beststrategy1_binary = 1 if beststrategy1>=5
(1,401 real changes made)

. replace beststrategy1_binary = . if beststrategy1==.
(206 real changes made, 206 to missing)

. 
. gen beststrategy2 = .
(2,226 missing values generated)

. replace beststrategy2 = 7 if strategy2=="Storngly agree" 
(0 real changes made)

. replace beststrategy2 = 6 if strategy2=="Agree" 
(545 real changes made)

. replace beststrategy2 = 5 if strategy2=="Somewhat agree"
(392 real changes made)

. replace beststrategy2 = 4 if strategy2=="Neither agree nor disagree"
(344 real changes made)

. replace beststrategy2 = 3 if strategy2=="Somewhat disagree" 
(86 real changes made)

. replace beststrategy2 = 2 if strategy2=="Disagree" 
(53 real changes made)

. replace beststrategy2 = 1 if strategy2=="Strongly disagree" 
(47 real changes made)

. 
. gen beststrategy2_binary = 0

. replace beststrategy2_binary = 1 if beststrategy2>=5
(1,696 real changes made)

. replace beststrategy2_binary = . if beststrategy2==.
(759 real changes made, 759 to missing)

. 
. *Pacifist 
. rename pacifist1 pacifist1_text

. rename pacifist2 pacifist2_text

. 
. gen pacifist1 = .
(2,226 missing values generated)

. replace pacifist1 = 7 if pacifist1_text=="Strongly agree" 
(204 real changes made)

. replace pacifist1 = 6 if pacifist1_text=="Agree" 
(257 real changes made)

. replace pacifist1 = 5 if pacifist1_text=="Somewhat agree"
(304 real changes made)

. replace pacifist1 = 4 if pacifist1_text=="Neither agree nor disagree"
(672 real changes made)

. replace pacifist1 = 3 if pacifist1_text=="Somewhat disagree" 
(199 real changes made)

. replace pacifist1 = 2 if pacifist1_text=="Disagree" 
(229 real changes made)

. replace pacifist1 = 1 if pacifist1_text=="Strongly disagree" 
(155 real changes made)

. 
. gen pacifist1_binary = 0

. replace pacifist1_binary = 1 if pacifist1>=5
(971 real changes made)

. replace pacifist1_binary = . if pacifist1==.
(206 real changes made, 206 to missing)

. 
. gen pacifist2 = .
(2,226 missing values generated)

. replace pacifist2 = 7 if pacifist2_text=="Strongly agree" 
(227 real changes made)

. replace pacifist2 = 6 if pacifist2_text=="Agree" 
(271 real changes made)

. replace pacifist2 = 5 if pacifist2_text=="Somewhat agree"
(264 real changes made)

. replace pacifist2 = 4 if pacifist2_text=="Neither agree nor disagree"
(642 real changes made)

. replace pacifist2 = 3 if pacifist2_text=="Somewhat disagree" 
(208 real changes made)

. replace pacifist2 = 2 if pacifist2_text=="Disagree" 
(239 real changes made)

. replace pacifist2 = 1 if pacifist2_text=="Strongly disagree" 
(151 real changes made)

. 
. gen pacifist2_binary = 0

. replace pacifist2_binary = 1 if pacifist2>=5
(986 real changes made)

. replace pacifist2_binary = . if pacifist2==.
(224 real changes made, 224 to missing)

. 
. *Warmonger 
. rename warmonger1 warmonger1_text

. rename warmonger2 warmonger2_text

. 
. gen warmonger1 = .
(2,226 missing values generated)

. replace warmonger1 = 7 if warmonger1_text=="Strongly agree" 
(151 real changes made)

. replace warmonger1 = 6 if warmonger1_text=="Agree" 
(175 real changes made)

. replace warmonger1 = 5 if warmonger1_text=="Somewhat agree"
(254 real changes made)

. replace warmonger1 = 4 if warmonger1_text=="Neither agree nor disagree"
(581 real changes made)

. replace warmonger1 = 3 if warmonger1_text=="Somewhat disagree" 
(243 real changes made)

. replace warmonger1 = 2 if warmonger1_text=="Disagree" 
(304 real changes made)

. replace warmonger1 = 1 if warmonger1_text=="Strongly disagree" 
(312 real changes made)

. 
. gen warmonger1_binary = 0

. replace warmonger1_binary = 1 if warmonger1>=5
(786 real changes made)

. replace warmonger1_binary = . if warmonger1==.
(206 real changes made, 206 to missing)

. 
. gen warmonger2 = .
(2,226 missing values generated)

. replace warmonger2 = 7 if warmonger2_text=="Strongly agree" 
(145 real changes made)

. replace warmonger2 = 6 if warmonger2_text=="Agree" 
(179 real changes made)

. replace warmonger2 = 5 if warmonger2_text=="Somewhat agree"
(212 real changes made)

. replace warmonger2 = 4 if warmonger2_text=="Neither agree nor disagree"
(550 real changes made)

. replace warmonger2 = 3 if warmonger2_text=="Somewhat disagree" 
(257 real changes made)

. replace warmonger2 = 2 if warmonger2_text=="Disagree" 
(344 real changes made)

. replace warmonger2 = 1 if warmonger2_text=="Strongly disagree" 
(315 real changes made)

. 
. gen warmonger2_binary = 0

. replace warmonger2_binary = 1 if warmonger2>=5
(760 real changes made)

. replace warmonger2_binary = . if warmonger2==.
(224 real changes made, 224 to missing)

. 
. *Moderate
. gen moderate = 0

. replace moderate = 1 if warmonger1<4 & pacifist1<4
(285 real changes made)

. replace moderate = . if warmonger1==. | pacifist1==.
(206 real changes made, 206 to missing)

. 
. *Competent 
. rename competent1 competent1_text

. 
. gen competent1 = .
(2,226 missing values generated)

. replace competent1 = 7 if competent1_text=="Strongly agree" 
(336 real changes made)

. replace competent1 = 6 if competent1_text=="Agree" 
(557 real changes made)

. replace competent1 = 5 if competent1_text=="Somewhat agree"
(376 real changes made)

. replace competent1 = 4 if competent1_text=="Neither agree nor disagree"
(483 real changes made)

. replace competent1 = 3 if competent1_text=="Somewhat disagree" 
(144 real changes made)

. replace competent1 = 2 if competent1_text=="Disagree" 
(70 real changes made)

. replace competent1 = 1 if competent1_text=="Strongly disagree" 
(54 real changes made)

. 
. gen competent1_binary = 0

. replace competent1_binary = 1 if competent1>=5
(1,475 real changes made)

. replace competent1_binary = . if competent1==.
(206 real changes made, 206 to missing)

. 
. *Tough 
. rename tough1 tough1_text

. 
. gen tough1 = .
(2,226 missing values generated)

. replace tough1 = 7 if tough1_text=="Strongly agree" 
(307 real changes made)

. replace tough1 = 6 if tough1_text=="Agree" 
(507 real changes made)

. replace tough1 = 5 if tough1_text=="Somewhat agree"
(405 real changes made)

. replace tough1 = 4 if tough1_text=="Neither agree nor disagree"
(431 real changes made)

. replace tough1 = 3 if tough1_text=="Somewhat disagree" 
(169 real changes made)

. replace tough1 = 2 if tough1_text=="Disagree" 
(121 real changes made)

. replace tough1 = 1 if tough1_text=="Strongly disagree" 
(80 real changes made)

. 
. gen tough1_binary = 0

. replace tough1_binary = 1 if tough1>=5
(1,425 real changes made)

. replace tough1_binary = . if tough1==.
(206 real changes made, 206 to missing)

. 
. *Trustworthy 
. rename trustworthy1 trustworthy1_text

. 
. gen trustworthy1 = .
(2,226 missing values generated)

. replace trustworthy1 = 7 if trustworthy1_text=="Strongly agree" 
(312 real changes made)

. replace trustworthy1 = 6 if trustworthy1_text=="Agree" 
(441 real changes made)

. replace trustworthy1 = 5 if trustworthy1_text=="Somewhat agree"
(329 real changes made)

. replace trustworthy1 = 4 if trustworthy1_text=="Neither agree nor disagree"
(626 real changes made)

. replace trustworthy1 = 3 if trustworthy1_text=="Somewhat disagree" 
(138 real changes made)

. replace trustworthy1 = 2 if trustworthy1_text=="Disagree" 
(94 real changes made)

. replace trustworthy1 = 1 if trustworthy1_text=="Strongly disagree" 
(80 real changes made)

. 
. gen trustworthy1_binary = 0

. replace trustworthy1_binary = 1 if trustworthy1>=5
(1,288 real changes made)

. replace trustworthy1_binary = . if trustworthy1==.
(206 real changes made, 206 to missing)

. 
. 
. ***Confounding Placebo (1 = Perceived President Non-White; 1 = White)
. gen nonwhite_placebo = 0

. replace nonwhite_placebo = 1 if race!="Caucasian/White"
(728 real changes made)

. replace nonwhite_placebo = . if race==""
(226 real changes made, 226 to missing)

. 
. 
. ***Manipulation Checks (1 = Passed; 0 = Failed)
. 
. *Name Check
. gen name_manipcheck = 0

. replace name_manipcheck = 1 if male==1 & male_name=="Eric" & name=="Eric"
(308 real changes made)

. replace name_manipcheck = 1 if male==1 & male_name=="Steven" & name=="Steven"
(319 real changes made)

. replace name_manipcheck = 1 if female==1 & female_name=="Erica" & name=="Erica"
(353 real changes made)

. replace name_manipcheck = 1 if female==1 & female_name=="Stephanie" & name=="Stephanie"
(374 real changes made)

. 
. *Policy Check
. gen policy_manipcheck = 0

. replace policy_manipcheck = 1 if statusquo==1 & action=="Maintained the U.S. military  presence in the Arctic"
(758 real changes made)

. replace policy_manipcheck = 1 if conciliatory==1 & action=="Decreased the U.S. military presence in the Arctic"
(771 real changes made)

. 
. *FP Orientation Check
. gen hawkdove_manipcheck = 0

. replace hawkdove_manipcheck = 1 if hawk==1 & hawkdove=="Usually favors military solutions over diplomatic ones"
(709 real changes made)

. replace hawkdove_manipcheck = 1 if dove==1 & hawkdove=="Usually favors diplomatic solutions over military ones"
(814 real changes made)

. 
. *Implied Gender Manip Check (i.e., got gender of leader right)
. gen implied_gender_manipcheck = 0

. replace implied_gender_manipcheck = 1 if (male==1) & (name=="Eric" | name=="Steven")
(694 real changes made)

. replace implied_gender_manipcheck = 1 if (female==1) & (name=="Erica" | name=="Stephanie")
(746 real changes made)

. 
. *Got At Least 2/3 Manipulation Checks Correct
. gen manip_total = name_manipcheck + policy_manipcheck + hawkdove_manipcheck

. 
. gen twothirds_manipcheck = 0

. replace twothirds_manipcheck = 1 if manip_total>=2
(1,554 real changes made)

. 
. *Got All Manipulation Checks Correct
. gen all_manipcheck = 0

. replace all_manipcheck = 1 if manip_total==3
(1,024 real changes made)

. 
. 
end of do-file

. 
. ********************************************************************************
. *                                                FIGURE 4: STUDY 2 PREMIA                                          
>                 *
. ********************************************************************************
. 
. ***Main Effect of Disposition -- Outcome 1, Binary DV
. reg disapproval1_binary hawksq hawkconc dovesq doveconc, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(4, 2137)        =     143.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2435
                                                Root MSE          =     .39106

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      hawksq |   .1940299   .0170969    11.35   0.000     .1605015    .2275582
    hawkconc |   .2849162   .0194965    14.61   0.000     .2466822    .3231502
      dovesq |    .054409    .009834     5.53   0.000     .0351238    .0736942
    doveconc |   .2728972   .0192764    14.16   0.000     .2350947    .3106997
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq, level(95)

 ( 1)  hawksq - hawkconc - dovesq + doveconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1276018   .0337743     3.78   0.000     .0613679    .1938358
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq, level(90)

 ( 1)  hawksq - hawkconc - dovesq + doveconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1276018   .0337743     3.78   0.000     .0720239    .1831797
------------------------------------------------------------------------------

. 
. matrix study2_dispo = J(1,5,.)

. matrix colnames study2_dispo = premia ll95 ul95 ll90 ul90

. matrix rownames study2_dispo = disposition

. matrix study2_dispo[1, 1] = .1276018*100

. matrix study2_dispo[1, 2] = .0613679*100

. matrix study2_dispo[1, 3] = .1938358*100

. matrix study2_dispo[1, 4] = .0720239*100

. matrix study2_dispo[1, 5] = .1831797*100

. matrix list study2_dispo

study2_dispo[1,5]
               premia      ll95      ul95      ll90      ul90
disposition  12.76018   6.13679  19.38358   7.20239  18.31797

. 
. ***Main Effect of Gender -- Outcome 1, Binary DV
. reg disapproval1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(4, 2137)        =     141.72
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2326
                                                Root MSE          =     .39386

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .1325967   .0145674     9.10   0.000     .1040289    .1611645
     femconc |         .3   .0197387    15.20   0.000     .2612909    .3387091
      malesq |   .1159696   .0139739     8.30   0.000     .0885656    .1433735
    maleconc |   .2575188   .0189757    13.57   0.000     .2203061    .2947315
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq, level(95)

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0258541   .0340173     0.76   0.447    -.0408563    .0925645
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq, level(90)

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0258541   .0340173     0.76   0.447    -.0301236    .0818318
------------------------------------------------------------------------------

. 
. matrix study2_gender = J(1,5,.)

. matrix colnames study2_gender = premia ll95 ul95 ll90 ul90

. matrix rownames study2_gender = gender

. matrix study2_gender[1, 1] = .0258541*100

. matrix study2_gender[1, 2] = -.0408563*100

. matrix study2_gender[1, 3] = .0925645*100

. matrix study2_gender[1, 4] = -.0301236*100

. matrix study2_gender[1, 5] = .0818318*100

. matrix list study2_gender

study2_gender[1,5]
          premia      ll95      ul95      ll90      ul90
gender   2.58541  -4.08563   9.25645  -3.01236   8.18318

. 
. *** Main Effect of Partisanship -- Outcome 1, Binary DV:
. reg disapproval1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(4, 2137)        =     141.68
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2324
                                                Root MSE          =     .39391

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .1228733   .0142869     8.60   0.000     .0948557     .150891
     demconc |   .2994455     .01971    15.19   0.000     .2607926    .3380983
       repsq |   .1259259   .0142903     8.81   0.000     .0979016    .1539502
     repconc |   .2580038   .0190052    13.58   0.000     .2207331    .2952744
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq, level(95)

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0444943   .0340296     1.31   0.191    -.0222402    .1112288
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq, level(90)

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0444943   .0340296     1.31   0.191    -.0115036    .1004922
------------------------------------------------------------------------------

. 
. matrix study2_partisan = J(1,5,.)

. matrix colnames study2_partisan = premia ll95 ul95 ll90 ul90

. matrix rownames study2_partisan = partisan

. matrix study2_partisan[1, 1] = .0444943*100

. matrix study2_partisan[1, 2] = -.0222402*100

. matrix study2_partisan[1, 3] = .1112288*100

. matrix study2_partisan[1, 4] =  -.0115036*100

. matrix study2_partisan[1, 5] = .1004922*100

. matrix list study2_partisan

study2_partisan[1,5]
            premia      ll95      ul95      ll90      ul90
partisan   4.44943  -2.22402  11.12288  -1.15036  10.04922

. 
. ***Create Figure 
. 
. coefplot (matrix(study2_gender[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel m
> labcolor(black) mlabposition(12) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_partisan[,1]), ci((2 3
> ) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcol
> or(black black) lwidth(.55 1.1))) (matrix(study2_dispo[,1]), ci((2 3) (4 5)) msymbol(T) msize(large) mfcolor(white)
>  mlcolor(black) mlabel mlabcolor(black) mlabposition(12) ciopts(lcolor(black black) lwidth(.55 1.1))), legend(off) 
> ylabel(1 `" "Gendered" "Peace Premium" "' 2  `" "Partisan" "Peace Premium" "' 3 `" "Dispositional" "Peace Premium" 
> "', labsize(medium)) xlabel(-10(5)25, labsize(medium)) xmtick(-10(1)25) xtitle("Peace Premia (in % Points)", size(m
> edlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(%4.1f)

. graph export "${results}/figure4.eps", replace
(file ~/Desktop/ISQ Replication/results/figure4.eps written in EPS format)

. 
. eststo clear

. 
. ********************************************************************************
. *                                        TABLE 3: STUDY 2 CO- AND OUT-PARTISANS                                    
> *
. ********************************************************************************
. 
. ************ Gender -- Binary DV ************
. 
. reg disapproval1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisa
> n 1.maleconc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent 
> political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(22, 1948)       =      25.13
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2684
                                                Root MSE          =     .38614

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   .2704895   .0780286     3.47   0.001     .1174612    .4235177
                        |
     femsq#out_partisan |
                   1 1  |    .001782   .0307035     0.06   0.954    -.0584332    .0619971
                        |
              1.femconc |   .3772614   .0762301     4.95   0.000     .2277603    .5267625
                        |
   femconc#out_partisan |
                   1 1  |   .1447205    .041165     3.52   0.000     .0639884    .2254525
                        |
               1.malesq |   .2085276   .0760267     2.74   0.006     .0594253      .35763
                        |
    malesq#out_partisan |
                   1 1  |   .0827684   .0294587     2.81   0.005     .0249945    .1405423
                        |
             1.maleconc |   .3523102   .0748712     4.71   0.000     .2054741    .4991463
                        |
  maleconc#out_partisan |
                   1 1  |   .0918739   .0406272     2.26   0.024     .0121966    .1715513
                        |
               democrat |   .0283497   .0175385     1.62   0.106    -.0060464    .0627458
                   dove |  -.0773862   .0174842    -4.43   0.000    -.1116759   -.0430966
             hostsexism |  -.0277355   .0104767    -2.65   0.008    -.0482823   -.0071888
            benevsexism |  -.0382409   .0080177    -4.77   0.000    -.0539652   -.0225166
         secordersexism |   .0084491   .0082941     1.02   0.308    -.0078171    .0247154
                hawkish |  -.0001003   .0116321    -0.01   0.993    -.0229129    .0227124
      female_respondent |   .0059275   .0184092     0.32   0.747    -.0301763    .0420314
political_identfication |   .0102413   .0042129     2.43   0.015      .001979    .0185036
              education |  -.0021965   .0045867    -0.48   0.632    -.0111919     .006799
                    hhi |   9.04e-06   .0000124     0.73   0.466    -.0000153    .0000334
                    age |   .0011222    .000563     1.99   0.046      .000018    .0022265
                  white |   .0041659   .0210975     0.20   0.843    -.0372102     .045542
            SexismOrder |  -.0236085   .0175211    -1.35   0.178    -.0579706    .0107536
       nonwhite_placebo |   .0030667   .0209936     0.15   0.884    -.0381055     .044239
-----------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Out-Partisan)
. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0968224   .0573943     1.69   0.092    -.0157383     .209383
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Co-Partisan)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0370106   .0433268    -0.85   0.393    -.1219823    .0479611
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan
> )+(1.malesq+1.malesq#1.out_partisan))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.out_partisan + 1.femconc#1.out_partisan + 1.malesq#1.out_partisan - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .133833   .0717991     1.86   0.062    -.0069782    .2746442
------------------------------------------------------------------------------

. 
. ************ Gender -- Full DV ************
. 
. reg disapproval1 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisan 1.mal
> econc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent politic
> al_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(22, 1948)       =     382.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8127
                                                Root MSE          =     1.5354

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   3.894346   .3186239    12.22   0.000     3.269467    4.519226
                        |
     femsq#out_partisan |
                   1 1  |   .1411211   .1372582     1.03   0.304    -.1280673    .4103094
                        |
              1.femconc |   4.447256   .3123078    14.24   0.000     3.834764    5.059749
                        |
   femconc#out_partisan |
                   1 1  |   .4908491   .1520027     3.23   0.001      .192744    .7889541
                        |
               1.malesq |   3.710635   .3118331    11.90   0.000     3.099073    4.322197
                        |
    malesq#out_partisan |
                   1 1  |   .4021808    .129043     3.12   0.002      .149104    .6552576
                        |
             1.maleconc |   4.466375   .3084872    14.48   0.000     3.861376    5.071375
                        |
  maleconc#out_partisan |
                   1 1  |   .2244978   .1504972     1.49   0.136    -.0706547    .5196504
                        |
               democrat |   .1622559    .069931     2.32   0.020     .0251085    .2994034
                   dove |  -.4294957   .0695843    -6.17   0.000    -.5659632   -.2930282
             hostsexism |   -.046129   .0444566    -1.04   0.300    -.1333164    .0410584
            benevsexism |  -.2128208   .0325613    -6.54   0.000    -.2766795   -.1489621
         secordersexism |  -.0044045   .0363423    -0.12   0.904    -.0756783    .0668694
                hawkish |  -.1095224   .0504376    -2.17   0.030    -.2084397   -.0106051
      female_respondent |   .2671233   .0734055     3.64   0.000     .1231617     .411085
political_identfication |   .0260095   .0176705     1.47   0.141    -.0086455    .0606645
              education |  -.0466505    .018591    -2.51   0.012    -.0831108   -.0101901
                    hhi |  -.0000361   .0000494    -0.73   0.465     -.000133    .0000608
                    age |   .0062837   .0022228     2.83   0.005     .0019244     .010643
                  white |  -.0855975   .0846781    -1.01   0.312    -.2516667    .0804717
            SexismOrder |  -.0500526   .0697504    -0.72   0.473    -.1868459    .0867407
       nonwhite_placebo |   .0978818   .0851306     1.15   0.250    -.0690748    .2648385
-----------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Out-Partisan)
. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3245805   .2257155     1.44   0.151    -.1180888    .7672499
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Co-Partisan)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.2028304   .1742103    -1.16   0.244    -.5444886    .1388278
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan
> )+(1.malesq+1.malesq#1.out_partisan))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.out_partisan + 1.femconc#1.out_partisan + 1.malesq#1.out_partisan - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5274109   .2850196     1.85   0.064    -.0315644    1.086386
------------------------------------------------------------------------------

. 
. ************ Gender -- Passed Manipulation Check / Binary DV ************
. 
. reg disapproval1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisa
> n 1.maleconc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent 
> political_identfication education hhi age white SexismOrder nonwhite_placebo if policy_manipcheck==1 & name_manipch
> eck==1, robust noconst

Linear regression                               Number of obs     =      1,150
                                                F(22, 1128)       =      18.44
                                                Prob > F          =     0.0000
                                                R-squared         =     0.3146
                                                Root MSE          =     .40578

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |    .049657   .1180119     0.42   0.674    -.1818905    .2812045
                        |
     femsq#out_partisan |
                   1 1  |   .0269207   .0416054     0.65   0.518     -.054712    .1085533
                        |
              1.femconc |   .2065119   .1128422     1.83   0.067    -.0148924    .4279161
                        |
   femconc#out_partisan |
                   1 1  |   .1426638   .0530936     2.69   0.007     .0384905     .246837
                        |
               1.malesq |  -.0282048   .1140867    -0.25   0.805    -.2520508    .1956412
                        |
    malesq#out_partisan |
                   1 1  |   .1641962   .0425647     3.86   0.000     .0806814     .247711
                        |
             1.maleconc |   .2027018   .1141384     1.78   0.076    -.0212457    .4266493
                        |
  maleconc#out_partisan |
                   1 1  |   .0705437   .0585975     1.20   0.229    -.0444286     .185516
                        |
               democrat |    .041065   .0247542     1.66   0.097    -.0075045    .0896345
                   dove |  -.0881755   .0240732    -3.66   0.000    -.1354088   -.0409421
             hostsexism |  -.0084185   .0141091    -0.60   0.551    -.0361015    .0192645
            benevsexism |  -.0202552   .0114485    -1.77   0.077     -.042718    .0022076
         secordersexism |   .0128282    .012586     1.02   0.308    -.0118664    .0375227
                hawkish |   .0055235   .0149031     0.37   0.711    -.0237175    .0347645
      female_respondent |  -.0047167   .0249177    -0.19   0.850     -.053607    .0441736
political_identfication |   .0163782    .006552     2.50   0.013     .0035228    .0292337
              education |   .0118382   .0067526     1.75   0.080    -.0014107    .0250872
                    hhi |   .0000199   .0000164     1.21   0.226    -.0000123    .0000521
                    age |   .0003468   .0007491     0.46   0.643     -.001123    .0018166
                  white |   .0156665   .0295816     0.53   0.596    -.0423746    .0737075
            SexismOrder |  -.0302751   .0241521    -1.25   0.210    -.0776633     .017113
       nonwhite_placebo |    .022515   .0286081     0.79   0.431    -.0336162    .0786461
-----------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Out-Partisan)
. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1353438   .0787142     1.72   0.086    -.0190988    .2897865
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Co-Partisan)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0740518   .0595564    -1.24   0.214    -.1909056     .042802
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan
> )+(1.malesq+1.malesq#1.out_partisan))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.out_partisan + 1.femconc#1.out_partisan + 1.malesq#1.out_partisan - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2093956    .098487     2.13   0.034     .0161572     .402634
------------------------------------------------------------------------------

. 
. ************ Gender -- Passed Manipulation Check / Full DV ************
. 
. reg disapproval1 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisan 1.mal
> econc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent politic
> al_identfication education hhi age white SexismOrder nonwhite_placebo if policy_manipcheck==1 & name_manipcheck==1,
>  robust noconst

Linear regression                               Number of obs     =      1,150
                                                F(22, 1128)       =     245.83
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8283
                                                Root MSE          =     1.5162

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   2.816367   .4604947     6.12   0.000     1.912844     3.71989
                        |
     femsq#out_partisan |
                   1 1  |   .1969847   .1739233     1.13   0.258    -.1442649    .5382342
                        |
              1.femconc |   3.680863   .4416419     8.33   0.000     2.814331    4.547395
                        |
   femconc#out_partisan |
                   1 1  |   .4573765    .182799     2.50   0.012     .0987122    .8160407
                        |
               1.malesq |   2.505896   .4504568     5.56   0.000     1.622068    3.389723
                        |
    malesq#out_partisan |
                   1 1  |   .7097051   .1761543     4.03   0.000     .3640781    1.055332
                        |
             1.maleconc |   3.677911   .4493575     8.18   0.000     2.796241    4.559582
                        |
  maleconc#out_partisan |
                   1 1  |   .1869253   .1989664     0.94   0.348    -.2034606    .5773112
                        |
               democrat |    .218511   .0925587     2.36   0.018     .0369045    .4001175
                   dove |  -.5422528   .0900336    -6.02   0.000     -.718905   -.3656006
             hostsexism |   .0079475   .0561312     0.14   0.887    -.1021858    .1180808
            benevsexism |  -.1201184   .0432154    -2.78   0.006      -.20491   -.0353269
         secordersexism |   .0199338   .0514087     0.39   0.698    -.0809337    .1208012
                hawkish |  -.0677701   .0622373    -1.09   0.276    -.1898841    .0543438
      female_respondent |   .1755922   .0928679     1.89   0.059    -.0066211    .3578055
political_identfication |    .054893   .0242699     2.26   0.024     .0072738    .1025122
              education |   .0512929   .0252012     2.04   0.042     .0018465    .1007393
                    hhi |   .0000597   .0000642     0.93   0.353    -.0000664    .0001857
                    age |   .0008254   .0027813     0.30   0.767    -.0046316    .0062824
                  white |   .0506481   .1125686     0.45   0.653    -.1702194    .2715156
            SexismOrder |  -.1190006   .0903228    -1.32   0.188    -.2962202     .058219
       nonwhite_placebo |   .0682938   .1102162     0.62   0.536    -.1479581    .2845457
-----------------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Out-Partisan)
. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4756518    .282263     1.69   0.092    -.0781678    1.029471
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Co-Partisan)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.3075198   .2296588    -1.34   0.181    -.7581263    .1430866
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan
> )+(1.malesq+1.malesq#1.out_partisan))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.out_partisan + 1.femconc#1.out_partisan + 1.malesq#1.out_partisan - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7831716   .3636419     2.15   0.031     .0696811    1.496662
------------------------------------------------------------------------------

. 
. eststo clear

. 
. ************ Gender -- IN-TEXT CALCULATION ************
. 
. reg disapproval1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisa
> n 1.maleconc 1.maleconc#out_partisan dove hostsexism benevsexism secordersexism hawkish female_respondent political
> _identfication education hhi age white SexismOrder nonwhite_placebo if policy_manipcheck==1 & name_manipcheck==1 & 
> democratic_respondent==1, robust noconst

Linear regression                               Number of obs     =        565
                                                F(21, 544)        =       8.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2945
                                                Root MSE          =     .39777

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   .2467475   .1712293     1.44   0.150    -.0896041     .583099
                        |
     femsq#out_partisan |
                   1 1  |   -.023765   .0595638    -0.40   0.690    -.1407682    .0932382
                        |
              1.femconc |   .3243394   .1605184     2.02   0.044     .0090277    .6396512
                        |
   femconc#out_partisan |
                   1 1  |   .0422488   .0699594     0.60   0.546    -.0951748    .1796724
                        |
               1.malesq |   .1417785   .1642629     0.86   0.388    -.1808888    .4644458
                        |
    malesq#out_partisan |
                   1 1  |   .2065097   .0590371     3.50   0.001      .090541    .3224783
                        |
             1.maleconc |   .2971863   .1629385     1.82   0.069    -.0228794    .6172521
                        |
  maleconc#out_partisan |
                   1 1  |    .021886   .0768247     0.28   0.776    -.1290233    .1727954
                        |
                   dove |  -.1681667    .034422    -4.89   0.000     -.235783   -.1005505
             hostsexism |  -.0078364   .0191366    -0.41   0.682     -.045427    .0297543
            benevsexism |  -.0231062    .016336    -1.41   0.158    -.0551956    .0089832
         secordersexism |   .0227384   .0167885     1.35   0.176    -.0102398    .0557167
                hawkish |  -.0032834   .0206482    -0.16   0.874    -.0438433    .0372765
      female_respondent |      .0243   .0341099     0.71   0.477    -.0427031    .0913032
political_identfication |   .0289869   .0230324     1.26   0.209    -.0162564    .0742301
              education |   .0048777   .0095575     0.51   0.610    -.0138964    .0236518
                    hhi |    .000049   .0000177     2.77   0.006     .0000143    .0000838
                    age |  -.0002398    .001054    -0.23   0.820    -.0023103    .0018307
                  white |   .0043059   .0388192     0.11   0.912    -.0719479    .0805598
            SexismOrder |  -.0747516   .0342297    -2.18   0.029    -.1419902    -.007513
       nonwhite_placebo |  -.0092778   .0390706    -0.24   0.812    -.0860255      .06747
-----------------------------------------------------------------------------------------

. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1728215   .0993324     1.74   0.082    -.0223005    .3679435
------------------------------------------------------------------------------

. 
. reg disapproval1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisa
> n 1.maleconc 1.maleconc#out_partisan dove hostsexism benevsexism secordersexism hawkish female_respondent political
> _identfication education hhi age white SexismOrder nonwhite_placebo if policy_manipcheck==1 & name_manipcheck==1 & 
> republican_respondent==1, robust noconst

Linear regression                               Number of obs     =        438
                                                F(21, 417)        =      11.37
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4390
                                                Root MSE          =     .40348

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |  -.3915268   .2233735    -1.75   0.080    -.8306051    .0475516
                        |
     femsq#out_partisan |
                   1 1  |   .1111032   .0650449     1.71   0.088    -.0167535    .2389599
                        |
              1.femconc |  -.0925534   .2280669    -0.41   0.685    -.5408575    .3557507
                        |
   femconc#out_partisan |
                   1 1  |   .2385188   .0911194     2.62   0.009     .0594082    .4176294
                        |
               1.malesq |  -.4259387   .2243231    -1.90   0.058    -.8668836    .0150062
                        |
    malesq#out_partisan |
                   1 1  |   .0684595    .055439     1.23   0.218    -.0405153    .1774343
                        |
             1.maleconc |  -.1014178   .2281027    -0.44   0.657    -.5497923    .3469567
                        |
  maleconc#out_partisan |
                   1 1  |   .1226176   .0976324     1.26   0.210    -.0692954    .3145305
                        |
                   dove |   .0115103   .0383365     0.30   0.764    -.0638466    .0868672
             hostsexism |   .0084511   .0227599     0.37   0.711    -.0362873    .0531895
            benevsexism |  -.0051545   .0189912    -0.27   0.786    -.0424849    .0321759
         secordersexism |  -.0041274   .0216421    -0.19   0.849    -.0466686    .0384139
                hawkish |   .0307128   .0271374     1.13   0.258    -.0226303     .084056
      female_respondent |  -.0152565   .0405617    -0.38   0.707    -.0949874    .0644743
political_identfication |   .0403803   .0259315     1.56   0.120    -.0105925    .0913531
              education |   .0182046   .0112684     1.62   0.107    -.0039453    .0403546
                    hhi |   .0000503    .000023     2.19   0.029     5.20e-06    .0000955
                    age |  -1.45e-06   .0012764    -0.00   0.999    -.0025103    .0025074
                  white |  -.0175336   .0591189    -0.30   0.767    -.1337417    .0986745
            SexismOrder |   .0348344   .0400146     0.87   0.385    -.0438211      .11349
       nonwhite_placebo |   .0745477   .0476418     1.56   0.118    -.0191003    .1681958
-----------------------------------------------------------------------------------------

. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |     .04771   .1212099     0.39   0.694    -.1905485    .2859685
------------------------------------------------------------------------------

. 
. ttesti 438 .04771 2.5367353 565 .1728215 2.3611042

Two-sample t test with equal variances
------------------------------------------------------------------------------
         |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       x |     438      .04771    .1212099    2.536735   -.1905168    .2859368
       y |     565    .1728215    .0993324    2.361104   -.0222851    .3679281
---------+--------------------------------------------------------------------
combined |   1,003    .1181866    .0770096    2.438907    -.032932    .2693051
---------+--------------------------------------------------------------------
    diff |           -.1251115    .1552961               -.4298547    .1796317
------------------------------------------------------------------------------
    diff = mean(x) - mean(y)                                      t =  -0.8056
Ho: diff = 0                                     degrees of freedom =     1001

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.2103         Pr(|T| > |t|) = 0.4206          Pr(T > t) = 0.7897

. 
. ********************************************************************************
. *                                                FIGURE 5: STUDY 2 MECHANISMS                                      
>         *
. ********************************************************************************
. 
. *** Gender -- Best Strategy
. reg beststrategy1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     777.44
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6023
                                                Root MSE          =     .48555

------------------------------------------------------------------------------
             |               Robust
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .6725838   .0208617    32.24   0.000     .6316711    .7134966
     femconc |   .4980695   .0219904    22.65   0.000     .4549433    .5411957
      malesq |   .6666667   .0211451    31.53   0.000     .6251982    .7081352
    maleconc |   .5322581   .0224261    23.73   0.000     .4882773    .5762388
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0401057     .04323     0.93   0.354    -.0446744    .1248858
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0401057     .04323     0.93   0.354     -.031034    .1112454
------------------------------------------------------------------------------

. 
. matrix study2_g_strategy = J(1,5,.)

. matrix colnames study2_g_strategy = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_strategy = gender

. matrix study2_g_strategy[1, 1] = .0401057*100

. matrix study2_g_strategy[1, 2] = -.0446744*100

. matrix study2_g_strategy[1, 3] = .1248858*100

. matrix study2_g_strategy[1, 4] = -.031034*100

. matrix study2_g_strategy[1, 5] = .1112454*100

. matrix list study2_g_strategy

study2_g_strategy[1,5]
          premia      ll95      ul95      ll90      ul90
gender   4.01057  -4.46744  12.48858   -3.1034  11.12454

. 
. *** Party -- Best Strategy
. reg beststrategy1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     778.33
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6026
                                                Root MSE          =     .48534

------------------------------------------------------------------------------
             |               Robust
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .6706587   .0210177    31.91   0.000       .62944    .7118774
     demconc |   .4882813   .0221129    22.08   0.000     .4449147    .5316478
       repsq |   .6686508   .0209874    31.86   0.000     .6274916      .70981
     repconc |   .5418327   .0222599    24.34   0.000     .4981779    .5854875
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0555593   .0432053     1.29   0.199    -.0291724     .140291
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0555593   .0432053     1.29   0.199    -.0155398    .1266584
------------------------------------------------------------------------------

. 
. matrix study2_p_strategy = J(1,5,.)

. matrix colnames study2_p_strategy = premia ll95 ul95 ll90 ul90

. matrix rownames study2_p_strategy = partisan

. matrix study2_p_strategy[1, 1] = .0555593*100

. matrix study2_p_strategy[1, 2] = -.0291724*100

. matrix study2_p_strategy[1, 3] = .140291*100

. matrix study2_p_strategy[1, 4] = -.0155398 *100

. matrix study2_p_strategy[1, 5] = .1266584*100

. matrix list study2_p_strategy

study2_p_strategy[1,5]
            premia      ll95      ul95      ll90      ul90
partisan   5.55593  -2.91724   14.0291  -1.55398  12.66584

. 
. *** Disposition -- Best Strategy
. reg beststrategy1_binary dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     820.73
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6070
                                                Root MSE          =     .48263

------------------------------------------------------------------------------
             |               Robust
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |    .747012   .0194219    38.46   0.000     .7089228    .7851011
    doveconc |    .518664   .0221686    23.40   0.000     .4751882    .5621399
      hawksq |   .5924453   .0219313    27.01   0.000      .549435    .6354556
    hawkconc |   .5108911   .0222665    22.94   0.000     .4672234    .5545588
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(95)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1467937   .0429585     3.42   0.001     .0625459    .2310414
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(90)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1467937   .0429585     3.42   0.001     .0761007    .2174867
------------------------------------------------------------------------------

. 
. matrix study2_d_strategy = J(1,5,.)

. matrix colnames study2_d_strategy = premia ll95 ul95 ll90 ul90

. matrix rownames study2_d_strategy = disposition

. matrix study2_d_strategy[1, 1] = .1467937*100

. matrix study2_d_strategy[1, 2] = .0625459*100

. matrix study2_d_strategy[1, 3] = .2310414*100

. matrix study2_d_strategy[1, 4] = .0761007*100

. matrix study2_d_strategy[1, 5] = .2174867*100

. matrix list study2_d_strategy

study2_d_strategy[1,5]
               premia      ll95      ul95      ll90      ul90
disposition  14.67937   6.25459  23.10414   7.61007  21.74867

. 
. *** Gender -- Competent
. reg competent1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     895.33
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6354
                                                Root MSE          =     .47904

------------------------------------------------------------------------------
             |               Robust
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .6883629   .0205902    33.43   0.000     .6479827    .7287431
     femconc |    .542471    .021911    24.76   0.000     .4995004    .5854417
      malesq |   .6967871   .0206177    33.80   0.000      .656353    .7372213
    maleconc |   .5887097   .0221164    26.62   0.000     .5453363    .6320831
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0378144   .0426412     0.89   0.375     -.045811    .1214398
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0378144   .0426412     0.89   0.375    -.0323564    .1079852
------------------------------------------------------------------------------

. 
. matrix study2_g_competent = J(1,5,.)

. matrix colnames study2_g_competent = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_competent = gender

. matrix study2_g_competent[1, 1] = .0378144*100

. matrix study2_g_competent[1, 2] = -.045811*100

. matrix study2_g_competent[1, 3] = .1214398*100

. matrix study2_g_competent[1, 4] = -.0323564*100

. matrix study2_g_competent[1, 5] = .1079852*100

. matrix list study2_g_competent

study2_g_competent[1,5]
          premia      ll95      ul95      ll90      ul90
gender   3.78144   -4.5811  12.14398  -3.23564  10.79852

. 
. *** Party -- Competent
. reg competent1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     900.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6361
                                                Root MSE          =     .47861

------------------------------------------------------------------------------
             |               Robust
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .6706587   .0210177    31.91   0.000       .62944    .7118774
     demconc |   .5351563   .0220643    24.25   0.000     .4918851    .5784274
       repsq |   .7142857   .0201427    35.46   0.000     .6747831    .7537883
     repconc |   .5956175    .021926    27.16   0.000     .5526176    .6386174
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0168342   .0426034     0.40   0.693    -.0667171    .1003856
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0168342   .0426034     0.40   0.693    -.0532743    .0869428
------------------------------------------------------------------------------

. 
. matrix study2_p_competent = J(1,5,.)

. matrix colnames study2_p_competent = premia ll95 ul95 ll90 ul90

. matrix rownames study2_p_competent = partisan

. matrix study2_p_competent[1, 1] = .0168342*100

. matrix study2_p_competent[1, 2] = -.0667171*100

. matrix study2_p_competent[1, 3] = .1003856*100

. matrix study2_p_competent[1, 4] = -.0532743*100

. matrix study2_p_competent[1, 5] = .0869428*100

. matrix list study2_p_competent

study2_p_competent[1,5]
            premia      ll95      ul95      ll90      ul90
partisan   1.68342  -6.67171  10.03856  -5.32743   8.69428

. 
. *** Disposition -- Competent
. reg competent1_binary dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     924.43
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6382
                                                Root MSE          =     .47725

------------------------------------------------------------------------------
             |               Robust
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |    .749004   .0193711    38.67   0.000     .7110145    .7869934
    doveconc |   .5933202   .0217943    27.22   0.000     .5505786    .6360619
      hawksq |   .6361829   .0214723    29.63   0.000     .5940726    .6782932
    hawkconc |   .5366337   .0222119    24.16   0.000      .493073    .5801944
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(95)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0561345   .0424813     1.32   0.187    -.0271773    .1394463
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(90)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0561345   .0424813     1.32   0.187    -.0137731    .1260421
------------------------------------------------------------------------------

. 
. matrix study2_d_competent = J(1,5,.)

. matrix colnames study2_d_competent = premia ll95 ul95 ll90 ul90

. matrix rownames study2_d_competent = disposition

. matrix study2_d_competent[1, 1] = .0561345*100

. matrix study2_d_competent[1, 2] = -.0271773*100

. matrix study2_d_competent[1, 3] = .1394463*100

. matrix study2_d_competent[1, 4] = -.0137731*100

. matrix study2_d_competent[1, 5] = .1260421*100

. matrix list study2_d_competent

study2_d_competent[1,5]
               premia      ll95      ul95      ll90      ul90
disposition   5.61345  -2.71773  13.94463  -1.37731  12.60421

. 
. *** Gender -- Moderate
. reg moderate femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =      83.56
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1479
                                                Root MSE          =     .34707

------------------------------------------------------------------------------
             |               Robust
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .1814596   .0171331    10.59   0.000     .1478591      .21506
     femconc |   .1158301   .0140749     8.23   0.000     .0882273    .1434329
      malesq |   .1606426    .016471     9.75   0.000     .1283406    .1929445
    maleconc |   .1068548   .0138851     7.70   0.000     .0796243    .1340854
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0118417   .0309149     0.38   0.702    -.0487869    .0724703
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0118417   .0309149     0.38   0.702    -.0390322    .0627157
------------------------------------------------------------------------------

. 
. matrix study2_g_moderate = J(1,5,.)

. matrix colnames study2_g_moderate = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_moderate = gender

. matrix study2_g_moderate[1, 1] = .0118417*100

. matrix study2_g_moderate[1, 2] = -.0487869*100

. matrix study2_g_moderate[1, 3] = .0724703*100

. matrix study2_g_moderate[1, 4] = -.0390322*100

. matrix study2_g_moderate[1, 5] = .0627157*100

. matrix list study2_g_moderate

study2_g_moderate[1,5]
          premia      ll95      ul95      ll90      ul90
gender   1.18417  -4.87869   7.24703  -3.90322   6.27157

. 
. *** Party -- Moderate
. reg moderate demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =      84.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1541
                                                Root MSE          =      .3458

------------------------------------------------------------------------------
             |               Robust
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .1377246   .0154113     8.94   0.000     .1075007    .1679484
     demconc |   .0839844     .01227     6.84   0.000     .0599211    .1080477
       repsq |   .2043651   .0179794    11.37   0.000     .1691049    .2396252
     repconc |   .1394422   .0154763     9.01   0.000     .1090911    .1697933
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0111827   .0308356    -0.36   0.717    -.0716557    .0492904
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0111827   .0308356    -0.36   0.717    -.0619261    .0395608
------------------------------------------------------------------------------

. 
. matrix study2_p_moderate = J(1,5,.)

. matrix colnames study2_p_moderate = premia ll95 ul95 ll90 ul90

. matrix rownames study2_p_moderate = partisan

. matrix study2_p_moderate[1, 1] = -.0111827*100

. matrix study2_p_moderate[1, 2] = -.0716557*100

. matrix study2_p_moderate[1, 3] = .0492904*100

. matrix study2_p_moderate[1, 4] = -.0619261*100

. matrix study2_p_moderate[1, 5] = .0395608*100

. matrix list study2_p_moderate

study2_p_moderate[1,5]
            premia      ll95      ul95      ll90      ul90
partisan  -1.11827  -7.16557   4.92904  -6.19261   3.95608

. 
. *** Disposition -- Moderate
. reg moderate dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =      83.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1514
                                                Root MSE          =     .34636

------------------------------------------------------------------------------
             |               Robust
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   .2031873   .0179765    11.30   0.000     .1679328    .2384417
    doveconc |   .1021611   .0134373     7.60   0.000     .0758086    .1285136
      hawksq |    .139165    .015448     9.01   0.000     .1088694    .1694607
    hawkconc |   .1207921   .0145161     8.32   0.000      .092324    .1492602
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(95)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0826532   .0308719     2.68   0.007     .0221091    .1431974
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(90)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0826532   .0308719     2.68   0.007     .0318501    .1334563
------------------------------------------------------------------------------

. 
. matrix study2_d_moderate = J(1,5,.)

. matrix colnames study2_d_moderate = premia ll95 ul95 ll90 ul90

. matrix rownames study2_d_moderate = disposition

. matrix study2_d_moderate[1, 1] = .0826532*100

. matrix study2_d_moderate[1, 2] = .0221091*100

. matrix study2_d_moderate[1, 3] = .1431974*100

. matrix study2_d_moderate[1, 4] = .0318501*100

. matrix study2_d_moderate[1, 5] = .1334563*100

. matrix list study2_d_moderate

study2_d_moderate[1,5]
               premia      ll95      ul95      ll90      ul90
disposition   8.26532   2.21091  14.31974   3.18501  13.34563

. 
. *** Gender -- Trustworthy
. reg trustworthy1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     592.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5399
                                                Root MSE          =     .49693

------------------------------------------------------------------------------
             |               Robust
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |    .591716   .0218506    27.08   0.000     .5488638    .6345682
     femconc |    .480695   .0219741    21.88   0.000     .4376006    .5237893
      malesq |   .5702811   .0222051    25.68   0.000     .5267338    .6138284
    maleconc |   .5020161   .0224727    22.34   0.000     .4579439    .5460884
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .042756   .0442538     0.97   0.334     -.044032     .129544
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .042756   .0442538     0.97   0.334    -.0300686    .1155806
------------------------------------------------------------------------------

. 
. matrix study2_g_trust = J(1,5,.)

. matrix colnames study2_g_trust = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_trust = gender

. matrix study2_g_trust[1, 1] = .042756*100

. matrix study2_g_trust[1, 2] = -.044032*100

. matrix study2_g_trust[1, 3] = .129544*100

. matrix study2_g_trust[1, 4] = -.0300686*100

. matrix study2_g_trust[1, 5] = .1155806*100

. matrix list study2_g_trust

study2_g_trust[1,5]
          premia      ll95      ul95      ll90      ul90
gender    4.2756   -4.4032   12.9544  -3.00686  11.55806

. 
. *** Party -- Trustworthy
. reg trustworthy1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     592.68
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5399
                                                Root MSE          =     .49691

------------------------------------------------------------------------------
             |               Robust
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .5708583   .0221348    25.79   0.000     .5274488    .6142678
     demconc |   .4785156   .0220986    21.65   0.000     .4351772     .521854
       repsq |   .5912698   .0219193    26.97   0.000      .548283    .6342567
     repconc |   .5039841   .0223375    22.56   0.000      .460177    .5477911
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0050569   .0442461     0.11   0.909     -.081716    .0918297
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0050569   .0442461     0.11   0.909    -.0677549    .0778687
------------------------------------------------------------------------------

. 
. matrix study2_p_trust = J(1,5,.)

. matrix colnames study2_p_trust = premia ll95 ul95 ll90 ul90

. matrix rownames study2_p_trust = partisan

. matrix study2_p_trust[1, 1] = .0050569*100

. matrix study2_p_trust[1, 2] = -.081716*100

. matrix study2_p_trust[1, 3] = .0918297*100

. matrix study2_p_trust[1, 4] = -.0677549*100

. matrix study2_p_trust[1, 5] = .0778687*100

. matrix list study2_p_trust

study2_p_trust[1,5]
            premia      ll95      ul95      ll90      ul90
partisan    .50569   -8.1716   9.18297  -6.77549   7.78687

. 
. *** Disposition -- Trustworthy
. reg trustworthy1_binary dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     652.41
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5568
                                                Root MSE          =      .4877

------------------------------------------------------------------------------
             |               Robust
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   .6992032   .0204888    34.13   0.000     .6590217    .7393847
    doveconc |   .5579568   .0220345    25.32   0.000     .5147439    .6011696
      hawksq |   .4632207   .0222555    20.81   0.000     .4195744     .506867
    hawkconc |   .4237624   .0220114    19.25   0.000      .380595    .4669298
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(95)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1017881    .043418     2.34   0.019     .0166393    .1869369
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(90)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1017881    .043418     2.34   0.019      .030339    .1732372
------------------------------------------------------------------------------

. 
. matrix study2_d_trust = J(1,5,.)

. matrix colnames study2_d_trust = premia ll95 ul95 ll90 ul90

. matrix rownames study2_d_trust = disposition

. matrix study2_d_trust[1, 1] = .1017881*100

. matrix study2_d_trust[1, 2] = .0166393*100

. matrix study2_d_trust[1, 3] = .1869369*100

. matrix study2_d_trust[1, 4] = .030339*100

. matrix study2_d_trust[1, 5] = .1732372*100

. matrix list study2_d_trust

study2_d_trust[1,5]
               premia      ll95      ul95      ll90      ul90
disposition  10.17881   1.66393  18.69369    3.0339  17.32372

. 
. *** Gender -- Tough
. reg tough1_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     897.23
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6276
                                                Root MSE          =     .47454

------------------------------------------------------------------------------
             |               Robust
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .7416174   .0194602    38.11   0.000     .7034531    .7797816
     femconc |    .507722   .0219879    23.09   0.000     .4646006    .5508434
      malesq |   .7028112   .0204999    34.28   0.000     .6626081    .7430144
    maleconc |   .4637097   .0224137    20.69   0.000     .4197533     .507666
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(95)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0052062   .0422467    -0.12   0.902     -.088058    .0776456
------------------------------------------------------------------------------

. lincom maleconc-malesq-femconc+femsq, level(90)

 ( 1)  femsq - femconc - malesq + maleconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0052062   .0422467    -0.12   0.902    -.0747278    .0643154
------------------------------------------------------------------------------

. 
. matrix study2_g_tough = J(1,5,.)

. matrix colnames study2_g_tough = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_tough = gender

. matrix study2_g_tough[1, 1] = -.0052062*100

. matrix study2_g_tough[1, 2] = -.088058*100

. matrix study2_g_tough[1, 3] = .0776456*100

. matrix study2_g_tough[1, 4] = -.0747278*100

. matrix study2_g_tough[1, 5] = .0643154*100

. matrix list study2_g_tough

study2_g_tough[1,5]
          premia      ll95      ul95      ll90      ul90
gender   -.52062   -8.8058   7.76456  -7.47278   6.43154

. 
. *** Party -- Tough
. reg tough1_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     892.81
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6273
                                                Root MSE          =     .47475

------------------------------------------------------------------------------
             |               Robust
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .7205589   .0200674    35.91   0.000     .6812038    .7599139
     demconc |   .4648438   .0220643    21.07   0.000     .4215726    .5081149
       repsq |   .7242063   .0199268    36.34   0.000      .685127    .7632857
     repconc |   .5079681   .0223354    22.74   0.000     .4641653     .551771
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(95)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0394769   .0422549     0.93   0.350     -.043391    .1223448
------------------------------------------------------------------------------

. lincom repconc-repsq-demconc+demsq, level(90)

 ( 1)  demsq - demconc - repsq + repconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0394769   .0422549     0.93   0.350    -.0300582    .1090121
------------------------------------------------------------------------------

. 
. matrix study2_p_tough = J(1,5,.)

. matrix colnames study2_p_tough = premia ll95 ul95 ll90 ul90

. matrix rownames study2_p_tough = partisan

. matrix study2_p_tough[1, 1] = .0394769*100

. matrix study2_p_tough[1, 2] = -.043391*100

. matrix study2_p_tough[1, 3] = .1223448*100

. matrix study2_p_tough[1, 4] = -.0300582*100

. matrix study2_p_tough[1, 5] = .1090121*100

. matrix list study2_p_tough

study2_p_tough[1,5]
            premia      ll95      ul95      ll90      ul90
partisan   3.94769   -4.3391  12.23448  -3.00582  10.90121

. 
. *** Disposition -- Tough
. reg tough1_binary dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(4, 2016)        =     915.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6296
                                                Root MSE          =     .47324

------------------------------------------------------------------------------
             |               Robust
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   .6812749   .0208184    32.72   0.000      .640447    .7221028
    doveconc |   .4459725   .0220542    20.22   0.000     .4027211    .4892239
      hawksq |   .7634195   .0189678    40.25   0.000     .7262209    .8006181
    hawkconc |   .5267327   .0222399    23.68   0.000     .4831171    .5703483
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(95)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0013844   .0421211    -0.03   0.974    -.0839898     .081221
------------------------------------------------------------------------------

. lincom hawkconc-hawksq-doveconc+dovesq, level(90)

 ( 1)  dovesq - doveconc - hawksq + hawkconc = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0013844   .0421211    -0.03   0.974    -.0706993    .0679305
------------------------------------------------------------------------------

. 
. matrix study2_d_tough = J(1,5,.)

. matrix colnames study2_d_tough = premia ll95 ul95 ll90 ul90

. matrix rownames study2_d_tough = disposition

. matrix study2_d_tough[1, 1] = -.0013844*100

. matrix study2_d_tough[1, 2] = -.0839898*100

. matrix study2_d_tough[1, 3] = .081221*100

. matrix study2_d_tough[1, 4] = -.0706993*100

. matrix study2_d_tough[1, 5] = .0679305*100

. matrix list study2_d_tough

study2_d_tough[1,5]
               premia      ll95      ul95      ll90      ul90
disposition   -.13844  -8.39898    8.1221  -7.06993   6.79305

. 
. coefplot (matrix(study2_g_strategy[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlab
> el mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_g_competent[,1]), 
> ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciop
> ts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_g_moderate[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mf
> color(black) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (
> matrix(study2_g_trust[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabpositi
> on(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_g_tough[,1]), ci((2 3) (4 5)) m
> symbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabposition(11) mlabcolor(black) ciopts(lcolor(black b
> lack) lwidth(.55 1.1))), legend(off) ylabel(.67 "Policy Credibility" .83  "Competence" 1  "Moderation" 1.17  "Trust
> worthiness" 1.33  "Toughness", labsize(medsmall)) xlabel(-15(5)25, labsize(medium)) xmtick(-15(1)25) xtitle("Gender
> ed Peace Premium" "(in % Points)", size(medlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(%4.1f)

. graph export "${results}/figure5a.eps", replace
(file ~/Desktop/ISQ Replication/results/figure5a.eps written in EPS format)

. 
. coefplot (matrix(study2_p_strategy[,1]), ci((2 3) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlab
> el mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_p_competent[,1]), 
> ci((2 3) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciop
> ts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_p_moderate[,1]), ci((2 3) (4 5)) msymbol(S) msize(large) mf
> color(white) mlcolor(black) mlabel mlabposition(11) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (
> matrix(study2_p_trust[,1]), ci((2 3) (4 5)) msymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabpositi
> on(1) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_p_tough[,1]), ci((2 3) (4 5)) ms
> ymbol(S) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcolor(black bl
> ack) lwidth(.55 1.1))), legend(off) ylabel(.67 "Policy Credibility" .83  "Competence" 1  "Moderation" 1.17  "Trustw
> orthiness" 1.33  "Toughness", labsize(medsmall)) xlabel(-15(5)25, labsize(medium)) xmtick(-15(1)25) xtitle("Partisa
> n Peace Premium" "(in % Points)", size(medlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(%4.1f)

. graph export "${results}/figure5c.eps", replace
(file ~/Desktop/ISQ Replication/results/figure5c.eps written in EPS format)

. 
. coefplot (matrix(study2_d_strategy[,1]), ci((2 3) (4 5)) msymbol(T) msize(large) mfcolor(white) mlcolor(black) mlab
> el mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_d_competent[,1]), 
> ci((2 3) (4 5)) msymbol(T) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciop
> ts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_d_moderate[,1]), ci((2 3) (4 5)) msymbol(T) msize(large) mf
> color(white) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (
> matrix(study2_d_trust[,1]), ci((2 3) (4 5)) msymbol(T) msize(large) mfcolor(white) mlcolor(black) mlabel mlabpositi
> on(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_d_tough[,1]), ci((2 3) (4 5)) m
> symbol(T) msize(large) mfcolor(white) mlcolor(black) mlabel mlabposition(11) mlabcolor(black) ciopts(lcolor(black b
> lack) lwidth(.55 1.1))), legend(off) ylabel(.67 "Policy Credibility" .83  "Competence" 1  "Moderation" 1.17  "Trust
> worthiness" 1.33  "Toughness", labsize(medsmall)) xlabel(-15(5)25, labsize(medium)) xmtick(-15(1)25) xtitle("Dispos
> itional Peace Premium" "(in % Points)", size(medlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(%4.1f)

. graph export "${results}/figure5d.eps", replace
(file ~/Desktop/ISQ Replication/results/figure5d.eps written in EPS format)

. 
. eststo clear

. 
. ********************************************************************************
. *                                FIGURE 5B: STUDY 2 OUT-PARTISAN MECHANISMS                                        
> *
. ********************************************************************************
. 
. *** Gender -- Best Strategy
. 
. reg beststrategy1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partis
> an 1.maleconc 1.maleconc#out_partisan democrat political_identfication, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(10, 2010)       =     315.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6036
                                                Root MSE          =     .48548

-----------------------------------------------------------------------------------------
                        |               Robust
   beststrategy1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   .6674386   .0351525    18.99   0.000     .5984995    .7363777
                        |
     femsq#out_partisan |
                   1 1  |   .0039634    .042061     0.09   0.925    -.0785243    .0864511
                        |
              1.femconc |   .5124572   .0364394    14.06   0.000     .4409942    .5839201
                        |
   femconc#out_partisan |
                   1 1  |  -.0413413   .0444965    -0.93   0.353    -.1286054    .0459227
                        |
               1.malesq |    .697166   .0349505    19.95   0.000     .6286229    .7657091
                        |
    malesq#out_partisan |
                   1 1  |  -.0802961    .042889    -1.87   0.061    -.1644076    .0038153
                        |
             1.maleconc |    .528302   .0365519    14.45   0.000     .4566185    .5999855
                        |
  maleconc#out_partisan |
                   1 1  |   .0011391    .045554     0.03   0.980    -.0881989    .0904771
                        |
               democrat |  -.0268855    .021616    -1.24   0.214    -.0692777    .0155067
political_identfication |   .0043901   .0045836     0.96   0.338    -.0045989    .0133792
-----------------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(95)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1128574   .0666945     1.69   0.091    -.0179401    .2436549
------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(90)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
bes~1_binary |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1128574   .0666945     1.69   0.091     .0031041    .2226106
------------------------------------------------------------------------------

. 
. matrix study2_g_strategy = J(1,5,.)

. matrix colnames study2_g_strategy = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_strategy = gender

. matrix study2_g_strategy[1, 1] = .1128574*100

. matrix study2_g_strategy[1, 2] = -.0179401*100

. matrix study2_g_strategy[1, 3] = .2436549*100

. matrix study2_g_strategy[1, 4] = .0031041*100

. matrix study2_g_strategy[1, 5] = .2226106*100

. matrix list study2_g_strategy

study2_g_strategy[1,5]
          premia      ll95      ul95      ll90      ul90
gender  11.28574  -1.79401  24.36549    .31041  22.26106

. 
. *** Gender -- Competent
. 
. reg competent1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisan 
> 1.maleconc 1.maleconc#out_partisan democrat political_identfication, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(10, 2010)       =     367.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6383
                                                Root MSE          =     .47785

-----------------------------------------------------------------------------------------
                        |               Robust
      competent1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   .7629783   .0342369    22.29   0.000     .6958348    .8301219
                        |
     femsq#out_partisan |
                   1 1  |  -.0817979   .0416886    -1.96   0.050    -.1635553   -.0000404
                        |
              1.femconc |   .5901321    .036345    16.24   0.000     .5188542    .6614099
                        |
   femconc#out_partisan |
                   1 1  |  -.0191013   .0442441    -0.43   0.666    -.1058704    .0676677
                        |
               1.malesq |   .7762356   .0343039    22.63   0.000     .7089606    .8435105
                        |
    malesq#out_partisan |
                   1 1  |  -.0934169   .0422056    -2.21   0.027    -.1761881   -.0106456
                        |
             1.maleconc |   .6480526   .0358398    18.08   0.000     .5777655    .7183396
                        |
  maleconc#out_partisan |
                   1 1  |  -.0472269   .0447625    -1.06   0.292    -.1350126    .0405588
                        |
               democrat |  -.0553215   .0213238    -2.59   0.010    -.0971407   -.0135024
political_identfication |  -.0030044   .0045039    -0.67   0.505    -.0118373    .0058285
-----------------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(95)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0281567   .0665448     0.42   0.672    -.1023473    .1586607
------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(90)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
competent1~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0281567   .0665448     0.42   0.672    -.0813502    .1376636
------------------------------------------------------------------------------

. 
. matrix study2_g_competent = J(1,5,.)

. matrix colnames study2_g_competent = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_competent = gender

. matrix study2_g_competent[1, 1] = .0281567*100

. matrix study2_g_competent[1, 2] = -.1023473*100

. matrix study2_g_competent[1, 3] = .1586607*100

. matrix study2_g_competent[1, 4] = -.0813502*100

. matrix study2_g_competent[1, 5] = .1376636*100

. matrix list study2_g_competent

study2_g_competent[1,5]
           premia       ll95       ul95       ll90       ul90
gender    2.81567  -10.23473   15.86607   -8.13502   13.76636

. 
. *** Gender -- Moderate
. 
. reg moderate 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisan 1.malecon
> c 1.maleconc#out_partisan democrat political_identfication, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(10, 2010)       =      33.65
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1549
                                                Root MSE          =     .34616

-----------------------------------------------------------------------------------------
                        |               Robust
               moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   .2222536   .0274794     8.09   0.000     .1683625    .2761446
                        |
     femsq#out_partisan |
                   1 1  |  -.0097201    .034459    -0.28   0.778    -.0772991     .057859
                        |
              1.femconc |   .1431357   .0235162     6.09   0.000      .097017    .1892543
                        |
   femconc#out_partisan |
                   1 1  |   .0224168   .0287597     0.78   0.436    -.0339851    .0788187
                        |
               1.malesq |   .1960083   .0268281     7.31   0.000     .1433945    .2486222
                        |
    malesq#out_partisan |
                   1 1  |   .0025142   .0333583     0.08   0.940    -.0629062    .0679346
                        |
             1.maleconc |   .1454627    .024023     6.06   0.000       .09835    .1925753
                        |
  maleconc#out_partisan |
                   1 1  |  -.0042476    .027951    -0.15   0.879    -.0590636    .0505684
                        |
               democrat |  -.0610226   .0154561    -3.95   0.000    -.0913342   -.0307109
political_identfication |  -.0015646   .0033613    -0.47   0.642    -.0081565    .0050273
-----------------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(95)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0103264   .0476783    -0.22   0.829    -.1038305    .0831778
------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(90)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
    moderate |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0103264   .0476783    -0.22   0.829    -.0887865    .0681337
------------------------------------------------------------------------------

. 
. matrix study2_g_moderate = J(1,5,.)

. matrix colnames study2_g_moderate = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_moderate = gender

. matrix study2_g_moderate[1, 1] = -.0103264*100

. matrix study2_g_moderate[1, 2] = -.1038305*100

. matrix study2_g_moderate[1, 3] = .0831778*100

. matrix study2_g_moderate[1, 4] = -.0887865*100

. matrix study2_g_moderate[1, 5] = .0681337*100

. matrix list study2_g_moderate

study2_g_moderate[1,5]
           premia       ll95       ul95       ll90       ul90
gender   -1.03264  -10.38305    8.31778   -8.87865    6.81337

. 
. *** Gender -- Trustworthy
. 
. reg trustworthy1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisa
> n 1.maleconc 1.maleconc#out_partisan democrat political_identfication, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(10, 2010)       =     239.89
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5425
                                                Root MSE          =     .49625

-----------------------------------------------------------------------------------------
                        |               Robust
    trustworthy1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   .6268236    .036287    17.27   0.000     .5556595    .6979876
                        |
     femsq#out_partisan |
                   1 1  |  -.0706747    .044215    -1.60   0.110    -.1573868    .0160374
                        |
              1.femconc |   .5171793   .0367902    14.06   0.000     .4450284    .5893303
                        |
   femconc#out_partisan |
                   1 1  |  -.0744183   .0443286    -1.68   0.093    -.1613531    .0125166
                        |
               1.malesq |   .6103252   .0366237    16.66   0.000     .5385008    .6821495
                        |
    malesq#out_partisan |
                   1 1  |  -.0833621   .0448735    -1.86   0.063    -.1713654    .0046413
                        |
             1.maleconc |    .529386   .0368847    14.35   0.000     .4570497    .6017223
                        |
  maleconc#out_partisan |
                   1 1  |  -.0543097   .0455583    -1.19   0.233    -.1436562    .0350368
                        |
               democrat |  -.0264945   .0221268    -1.20   0.231    -.0698884    .0168993
political_identfication |   .0022581   .0047275     0.48   0.633    -.0070132    .0115294
-----------------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(95)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .061501   .0680569     0.90   0.366    -.0719685    .1949705
------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(90)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
trustworth~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .061501   .0680569     0.90   0.366    -.0504943    .1734963
------------------------------------------------------------------------------

. 
. matrix study2_g_trust = J(1,5,.)

. matrix colnames study2_g_trust = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_trust = gender

. matrix study2_g_trust[1, 1] = .061501*100

. matrix study2_g_trust[1, 2] = -.0719685*100

. matrix study2_g_trust[1, 3] = .1949705*100

. matrix study2_g_trust[1, 4] = -.0504943*100

. matrix study2_g_trust[1, 5] = .1734963*100

. matrix list study2_g_trust

study2_g_trust[1,5]
          premia      ll95      ul95      ll90      ul90
gender    6.1501  -7.19685  19.49705  -5.04943  17.34963

. 
. *** Gender -- Tough
. 
. reg tough1_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisan 1.ma
> leconc 1.maleconc#out_partisan democrat political_identfication, robust noconst

Linear regression                               Number of obs     =      2,020
                                                F(10, 2010)       =     362.63
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6291
                                                Root MSE          =      .4743

-----------------------------------------------------------------------------------------
                        |               Robust
          tough1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   .7595592    .033299    22.81   0.000     .6942551    .8248633
                        |
     femsq#out_partisan |
                   1 1  |  -.0129739   .0393958    -0.33   0.742    -.0902348    .0642869
                        |
              1.femconc |   .5351056   .0361487    14.80   0.000     .4642128    .6059985
                        |
   femconc#out_partisan |
                   1 1  |  -.0349699   .0444229    -0.79   0.431    -.1220897    .0521499
                        |
               1.malesq |   .7485752   .0337245    22.20   0.000     .6824365    .8147139
                        |
    malesq#out_partisan |
                   1 1  |  -.0781252   .0418005    -1.87   0.062     -.160102    .0038515
                        |
             1.maleconc |    .505905   .0363704    13.91   0.000     .4345774    .5772327
                        |
  maleconc#out_partisan |
                   1 1  |  -.0710222    .045285    -1.57   0.117    -.1598326    .0177882
                        |
               democrat |  -.0258751   .0211307    -1.22   0.221    -.0673155    .0155652
political_identfication |   .0001624   .0044994     0.04   0.971    -.0086615    .0089864
-----------------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(95)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0108823   .0652956     0.17   0.868    -.1171717    .1389364
------------------------------------------------------------------------------

. lincom (1.maleconc+1.maleconc#1.out_partisan)-(1.malesq+1.malesq#1.out_partisan)-(1.femconc+1.femconc#1.out_partisa
> n)+(1.femsq+1.femsq#1.out_partisan), level(90)

 ( 1)  1.femsq + 1.femsq#1.out_partisan - 1.femconc - 1.femconc#1.out_partisan - 1.malesq - 1.malesq#1.out_partisan +
       1.maleconc + 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
tough1_bin~y |      Coef.   Std. Err.      t    P>|t|     [90% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0108823   .0652956     0.17   0.868    -.0965688    .1183335
------------------------------------------------------------------------------

. 
. matrix study2_g_tough = J(1,5,.)

. matrix colnames study2_g_tough = premia ll95 ul95 ll90 ul90

. matrix rownames study2_g_tough = gender

. matrix study2_g_tough[1, 1] = .0108823*100

. matrix study2_g_tough[1, 2] = -.1171717*100

. matrix study2_g_tough[1, 3] = .1389364*100

. matrix study2_g_tough[1, 4] = -.0965688*100

. matrix study2_g_tough[1, 5] = .1183335*100

. matrix list study2_g_tough

study2_g_tough[1,5]
           premia       ll95       ul95       ll90       ul90
gender    1.08823  -11.71717   13.89364   -9.65688   11.83335

. 
. coefplot (matrix(study2_g_strategy[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlab
> el mlabposition(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_g_competent[,1]), 
> ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabposition(12) mlabcolor(black) ciop
> ts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_g_moderate[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mf
> color(black) mlcolor(black) mlabel mlabposition(11) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (
> matrix(study2_g_trust[,1]), ci((2 3) (4 5)) msymbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabpositi
> on(12) mlabcolor(black) ciopts(lcolor(black black) lwidth(.55 1.1))) (matrix(study2_g_tough[,1]), ci((2 3) (4 5)) m
> symbol(O) msize(large) mfcolor(black) mlcolor(black) mlabel mlabposition(1) mlabcolor(black) ciopts(lcolor(black bl
> ack) lwidth(.55 1.1))), legend(off) ylabel(.67 "Policy Credibility" .83  "Competence" 1  "Moderation" 1.17  "Trustw
> orthiness" 1.33  "Toughness", labsize(medsmall)) xlabel(-20(5)30, labsize(medium)) xmtick(-20(1)30) xtitle("Out-Par
> tisan Gendered Peace Premium" "(in % Points)", size(medlarge)) xline(0, lcolor(cranberry) lpatt(solid)) xvarformat(
> %4.1f)

. graph export "${results}/figure5b.eps", replace
(file ~/Desktop/ISQ Replication/results/figure5b.eps written in EPS format)

. 
. ********************************************************************************
. *                                                        TABLE 4: STUDY 2 SUCCESS                                  
>                 *
. ********************************************************************************
. 
. *Gender -- Binary DV
. reg disapproval2_binary femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,005
                                                F(4, 2001)        =      38.31
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0749
                                                Root MSE          =     .25623

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .0717131   .0115272     6.22   0.000     .0491067    .0943196
     femconc |   .0912621   .0127027     7.18   0.000     .0663503     .116174
      malesq |   .0443548   .0092536     4.79   0.000     .0262071    .0625026
    maleconc |   .0752033   .0119012     6.32   0.000     .0518631    .0985434
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0112994   .0228364    -0.49   0.621    -.0560851    .0334862
------------------------------------------------------------------------------

. 
. *Gender -- Full DV
. reg disapproval2 femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,005
                                                F(4, 2001)        =    1482.54
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7474
                                                Root MSE          =     1.4158

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   2.418327   .0637511    37.93   0.000     2.293301    2.543352
     femconc |   2.500971    .064779    38.61   0.000     2.373929    2.628012
      malesq |   2.364919   .0603742    39.17   0.000     2.246517    2.483322
    maleconc |   2.443089   .0638021    38.29   0.000     2.317964    2.568215
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq    

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0044741   .1263973     0.04   0.972      -.24341    .2523582
------------------------------------------------------------------------------

.         
. *Gender -- Passed Manipulation Check / Binary DV
. reg disapproval2_binary femsq femconc malesq maleconc if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,160
                                                F(4, 1156)        =      19.52
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0682
                                                Root MSE          =     .24258

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .0686275   .0144777     4.74   0.000     .0402219     .097033
     femconc |   .0733945   .0144463     5.08   0.000     .0450507    .1017383
      malesq |   .0300752   .0104902     2.87   0.004     .0094933    .0506571
    maleconc |   .0766284   .0164935     4.65   0.000     .0442678    .1089889
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0417861   .0282909    -1.48   0.140    -.0972935    .0137212
------------------------------------------------------------------------------

. 
. *Gender -- Passed Manipulation Check / Full DV
. reg disapproval2 femsq femconc malesq maleconc if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,160
                                                F(4, 1156)        =     810.06
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7359
                                                Root MSE          =     1.3688

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   2.294118   .0808213    28.39   0.000     2.135545    2.452691
     femconc |   2.330275    .076421    30.49   0.000     2.180336    2.480215
      malesq |   2.176692   .0761322    28.59   0.000     2.027319    2.326064
    maleconc |   2.306513   .0879807    26.22   0.000     2.133894    2.479133
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0936641   .1609626    -0.58   0.561    -.4094757    .2221475
------------------------------------------------------------------------------

. 
. *Gender Out-Partisan -- Binary DV
. reg disapproval2_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisa
> n 1.maleconc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent 
> political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(22, 1948)       =       6.92
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0993
                                                Root MSE          =     .25261

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |    .095031   .0500412     1.90   0.058    -.0031089    .1931709
                        |
     femsq#out_partisan |
                   1 1  |   .0120367   .0233388     0.52   0.606     -.033735    .0578084
                        |
              1.femconc |   .0982008   .0513296     1.91   0.056    -.0024658    .1988675
                        |
   femconc#out_partisan |
                   1 1  |   .0452172   .0265947     1.70   0.089    -.0069398    .0973743
                        |
               1.malesq |   .0498595   .0485585     1.03   0.305    -.0453725    .1450915
                        |
    malesq#out_partisan |
                   1 1  |   .0439509   .0195188     2.25   0.024     .0056709    .0822309
                        |
             1.maleconc |   .0790381   .0480722     1.64   0.100    -.0152403    .1733164
                        |
  maleconc#out_partisan |
                   1 1  |    .055531   .0254087     2.19   0.029     .0056999    .1053621
                        |
               democrat |   .0097656   .0115192     0.85   0.397    -.0128256    .0323569
                   dove |  -.0147216   .0113925    -1.29   0.196    -.0370643    .0076212
             hostsexism |   .0208464   .0068688     3.03   0.002     .0073754    .0343174
            benevsexism |  -.0192923   .0059636    -3.24   0.001    -.0309879   -.0075966
         secordersexism |   .0018272   .0063313     0.29   0.773    -.0105896     .014244
                hawkish |  -.0101485   .0086117    -1.18   0.239    -.0270376    .0067406
      female_respondent |   .0318903   .0117134     2.72   0.007     .0089182    .0548625
political_identfication |  -.0003268   .0026857    -0.12   0.903    -.0055939    .0049404
              education |   .0017438   .0029835     0.58   0.559    -.0041074     .007595
                    hhi |   3.37e-07   8.70e-06     0.04   0.969    -.0000167    .0000174
                    age |   -.000448   .0003743    -1.20   0.231     -.001182     .000286
                  white |   .0031573   .0151261     0.21   0.835    -.0265078    .0328224
            SexismOrder |  -.0037934   .0114992    -0.33   0.742    -.0263455    .0187587
       nonwhite_placebo |   .0096052    .014322     0.67   0.503    -.0184828    .0376933
-----------------------------------------------------------------------------------------

. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0044083   .0398169    -0.11   0.912    -.0824965    .0736799
------------------------------------------------------------------------------

. 
. *Gender Out-Partisan -- Full DV
. reg disapproval2 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisan 1.mal
> econc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent politic
> al_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(22, 1948)       =     291.38
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7672
                                                Root MSE          =     1.3604

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   3.029824   .2679406    11.31   0.000     2.504343    3.555304
                        |
     femsq#out_partisan |
                   1 1  |   .0999058   .1241998     0.80   0.421    -.1436726    .3434843
                        |
              1.femconc |   3.056099   .2734263    11.18   0.000      2.51986    3.592338
                        |
   femconc#out_partisan |
                   1 1  |   .2219227    .129908     1.71   0.088    -.0328505    .4766959
                        |
               1.malesq |   2.831746   .2642551    10.72   0.000     2.313494    3.349999
                        |
    malesq#out_partisan |
                   1 1  |   .4248753   .1203994     3.53   0.000       .18875    .6610005
                        |
             1.maleconc |   2.963419   .2629293    11.27   0.000     2.447766    3.479071
                        |
  maleconc#out_partisan |
                   1 1  |   .2990219   .1281484     2.33   0.020     .0476994    .5503443
                        |
               democrat |    .125014   .0615354     2.03   0.042     .0043318    .2456962
                   dove |  -.2123837   .0616661    -3.44   0.001    -.3333221   -.0914452
             hostsexism |   .2021194   .0383339     5.27   0.000     .1269396    .2772992
            benevsexism |   -.143221   .0306443    -4.67   0.000      -.20332    -.083122
         secordersexism |  -.0541689   .0335213    -1.62   0.106    -.1199102    .0115725
                hawkish |  -.0872096    .044729    -1.95   0.051    -.1749314    .0005122
      female_respondent |   .2732938   .0632765     4.32   0.000     .1491971    .3973905
political_identfication |  -.0026764   .0148553    -0.18   0.857    -.0318103    .0264575
              education |  -.0232939   .0161872    -1.44   0.150      -.05504    .0084523
                    hhi |  -.0000616   .0000472    -1.31   0.191    -.0001541    .0000309
                    age |  -.0048001   .0019711    -2.44   0.015    -.0086658   -.0009344
                  white |  -.0746707   .0783374    -0.95   0.341    -.2283046    .0789632
            SexismOrder |  -.0472504   .0619226    -0.76   0.446    -.1686918     .074191
       nonwhite_placebo |   .1414092   .0748687     1.89   0.059     -.005422    .2882403
-----------------------------------------------------------------------------------------

. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1424731   .1985194     0.72   0.473    -.2468597    .5318058
------------------------------------------------------------------------------

.         
. *Gender Out-Partisan -- Passed Manipulation Check / Binary DV
. reg disapproval2_binary 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisa
> n 1.maleconc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent 
> political_identfication education hhi age white SexismOrder nonwhite_placebo if policy_manipcheck==1 & name_manipch
> eck==1, robust noconst

Linear regression                               Number of obs     =      1,150
                                                F(22, 1128)       =       3.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0989
                                                Root MSE          =     .23982

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |    .011978   .0692649     0.17   0.863    -.1239245    .1478804
                        |
     femsq#out_partisan |
                   1 1  |   .0009737   .0290771     0.03   0.973    -.0560775    .0580249
                        |
              1.femconc |   .0059575   .0691314     0.09   0.931    -.1296831    .1415982
                        |
   femconc#out_partisan |
                   1 1  |   .0169619   .0292531     0.58   0.562    -.0404347    .0743584
                        |
               1.malesq |  -.0336343   .0664855    -0.51   0.613    -.1640834    .0968149
                        |
    malesq#out_partisan |
                   1 1  |   .0146415   .0215103     0.68   0.496    -.0275631    .0568462
                        |
             1.maleconc |  -.0057272   .0632385    -0.09   0.928    -.1298055    .1183512
                        |
  maleconc#out_partisan |
                   1 1  |   .0717185    .035468     2.02   0.043     .0021279    .1413091
                        |
               democrat |   .0242792   .0146601     1.66   0.098    -.0044848    .0530433
                   dove |  -.0026222   .0139311    -0.19   0.851     -.029956    .0247117
             hostsexism |   .0222511   .0088171     2.52   0.012     .0049513    .0395508
            benevsexism |  -.0186749   .0075972    -2.46   0.014    -.0335812   -.0037687
         secordersexism |   .0058901   .0084741     0.70   0.487    -.0107368     .022517
                hawkish |  -.0074539   .0104856    -0.71   0.477    -.0280273    .0131196
      female_respondent |   .0288772   .0139004     2.08   0.038     .0016037    .0561508
political_identfication |   -.001443    .003515    -0.41   0.681    -.0083396    .0054536
              education |   .0112073   .0038724     2.89   0.004     .0036094    .0188052
                    hhi |   .0000107   7.98e-06     1.34   0.181    -4.98e-06    .0000263
                    age |  -.0003826   .0004458    -0.86   0.391    -.0012572    .0004921
                  white |  -.0078977   .0189203    -0.42   0.676    -.0450207    .0292252
            SexismOrder |   .0124858   .0143049     0.87   0.383    -.0155814    .0405531
       nonwhite_placebo |   .0109182   .0172983     0.63   0.528    -.0230222    .0448586
-----------------------------------------------------------------------------------------

. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0750164   .0475704    -1.58   0.115    -.1683527    .0183199
------------------------------------------------------------------------------

. 
. *Gender Out-Partisan -- Passed Manipulation Check / Full DV
. reg disapproval2 1.femsq 1.femsq#out_partisan 1.femconc 1.femconc#out_partisan 1.malesq 1.malesq#out_partisan 1.mal
> econc 1.maleconc#out_partisan democrat dove hostsexism benevsexism secordersexism hawkish female_respondent politic
> al_identfication education hhi age white SexismOrder nonwhite_placebo if policy_manipcheck==1 & name_manipcheck==1,
>  robust noconst

Linear regression                               Number of obs     =      1,150
                                                F(22, 1128)       =     163.18
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7549
                                                Root MSE          =     1.3267

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   2.211505   .3831212     5.77   0.000     1.459795    2.963216
                        |
     femsq#out_partisan |
                   1 1  |   .0521591   .1595189     0.33   0.744    -.2608279    .3651462
                        |
              1.femconc |    2.18691   .3847756     5.68   0.000     1.431953    2.941866
                        |
   femconc#out_partisan |
                   1 1  |   .1857691   .1497278     1.24   0.215    -.1080073    .4795454
                        |
               1.malesq |   1.889334   .3797111     4.98   0.000     1.144315    2.634354
                        |
    malesq#out_partisan |
                   1 1  |   .5443348   .1543738     3.53   0.000     .2414426    .8472269
                        |
             1.maleconc |   2.069989   .3666653     5.65   0.000     1.350566    2.789412
                        |
  maleconc#out_partisan |
                   1 1  |    .514933   .1796417     2.87   0.004     .1624636    .8674024
                        |
               democrat |   .1869273   .0801239     2.33   0.020     .0297187    .3441358
                   dove |  -.2471243   .0779374    -3.17   0.002    -.4000429   -.0942057
             hostsexism |   .1805958   .0482769     3.74   0.000     .0858732    .2753184
            benevsexism |  -.1268139   .0397978    -3.19   0.001       -.2049   -.0487278
         secordersexism |   -.027282   .0460246    -0.59   0.553    -.1175855    .0630214
                hawkish |  -.0389432   .0540577    -0.72   0.471    -.1450083    .0671218
      female_respondent |   .1963595    .079037     2.48   0.013     .0412835    .3514355
political_identfication |   .0024945    .020606     0.12   0.904    -.0379359    .0429249
              education |   .0615255   .0217266     2.83   0.005     .0188965    .1041545
                    hhi |  -.0000439   .0000581    -0.76   0.450    -.0001579    .0000701
                    age |  -.0046908   .0024316    -1.93   0.054    -.0094618    .0000801
                  white |   .0323704   .1025487     0.32   0.752    -.1688374    .2335781
            SexismOrder |   .0031473   .0793002     0.04   0.968    -.1524451    .1587398
       nonwhite_placebo |   .0688752   .0937029     0.74   0.462    -.1149764    .2527269
-----------------------------------------------------------------------------------------

. lincom (1.femconc+1.femconc#1.out_partisan)-(1.femsq+1.femsq#1.out_partisan)-(1.maleconc+1.maleconc#1.out_partisan)
> +(1.malesq+1.malesq#1.out_partisan)

 ( 1)  - 1.femsq - 1.femsq#1.out_partisan + 1.femconc + 1.femconc#1.out_partisan + 1.malesq + 1.malesq#1.out_partisan
       - 1.maleconc - 1.maleconc#1.out_partisan = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0422384   .2531277    -0.17   0.868    -.5388926    .4544158
------------------------------------------------------------------------------

. 
. *Partisan -- Binary DV
. reg disapproval2_binary demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,005
                                                F(4, 2001)        =      38.24
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0734
                                                Root MSE          =     .25643

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |       .062   .0107956     5.74   0.000     .0408282    .0831718
     demconc |   .0884086   .0125957     7.02   0.000     .0637066    .1131107
       repsq |   .0542169   .0101574     5.34   0.000     .0342967     .074137
     repconc |   .0783133   .0120511     6.50   0.000     .0546791    .1019474
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0023123   .0228823     0.10   0.920    -.0425633    .0471878
------------------------------------------------------------------------------

. 
. *Partisan -- Full DV
. reg disapproval2 demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,005
                                                F(4, 2001)        =    1484.69
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7478
                                                Root MSE          =     1.4146

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |      2.408    .062569    38.49   0.000     2.285293    2.530707
     demconc |   2.563851   .0665506    38.52   0.000     2.433335    2.694366
       repsq |   2.375502   .0616522    38.53   0.000     2.254593    2.496411
     repconc |   2.379518   .0616683    38.59   0.000     2.258577    2.500459
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq      

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1518346   .1262847     1.20   0.229    -.0958287    .3994979
------------------------------------------------------------------------------

.         
. *Partisan -- Passed Manipulation Check / Binary DV
. reg disapproval2_binary demsq demconc repsq repconc if policy_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,529
                                                F(4, 1525)        =      27.06
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0692
                                                Root MSE          =     .24829

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .0607735   .0125735     4.83   0.000     .0361103    .0854367
     demconc |   .0822622   .0139493     5.90   0.000     .0549003    .1096241
       repsq |   .0454545   .0104811     4.34   0.000     .0248956    .0660135
     repconc |   .0759162   .0135694     5.59   0.000     .0492996    .1025329
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq      

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   -.008973   .0254295    -0.35   0.724    -.0588535    .0409075
------------------------------------------------------------------------------

. 
. *Partisan -- Passed Manipulation Check / Full DV
. reg disapproval2 demsq demconc repsq repconc if policy_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,529
                                                F(4, 1525)        =    1072.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7370
                                                Root MSE          =     1.3737

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |    2.30663    .071649    32.19   0.000     2.166089    2.447171
     demconc |   2.421594   .0756117    32.03   0.000      2.27328    2.569908
       repsq |   2.234848   .0652133    34.27   0.000     2.106931    2.362766
     repconc |   2.217277   .0683014    32.46   0.000     2.083303    2.351252
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq      

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .132535   .1406007     0.94   0.346    -.1432562    .4083262
------------------------------------------------------------------------------

. 
. *Disposition -- Binary DV
. reg disapproval2_binary dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,005
                                                F(4, 2001)        =      38.33
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0754
                                                Root MSE          =     .25616

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   .0401606   .0088068     4.56   0.000     .0228892    .0574321
    doveconc |   .0851485   .0124323     6.85   0.000     .0607669    .1095301
      hawksq |       .076   .0118629     6.41   0.000      .052735     .099265
    hawkconc |   .0816733   .0122355     6.68   0.000     .0576777    .1056689
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq

 ( 1)  - dovesq + doveconc + hawksq - hawkconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0393146   .0228595     1.72   0.086    -.0055164    .0841455
------------------------------------------------------------------------------

. 
. *Disposition -- Full DV
. reg disapproval2 dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,005
                                                F(4, 2001)        =    1497.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7495
                                                Root MSE          =     1.4098

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   2.202811   .0581355    37.89   0.000     2.088799    2.316824
    doveconc |   2.455446   .0660171    37.19   0.000     2.325976    2.584915
      hawksq |       2.58   .0647423    39.85   0.000     2.453031    2.706969
    hawkconc |    2.49004   .0625961    39.78   0.000     2.367279      2.6128
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq  

 ( 1)  - dovesq + doveconc + hawksq - hawkconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3425945   .1258882     2.72   0.007     .0957089    .5894801
------------------------------------------------------------------------------

.         
. *Disposition -- Passed Manipulation Check / Binary DV
. reg disapproval2_binary dovesq doveconc hawksq hawkconc if policy_manipcheck==1 & hawkdove_manipcheck==1, robust no
> const

Linear regression                               Number of obs     =      1,293
                                                F(4, 1289)        =      21.46
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0705
                                                Root MSE          =     .24019

------------------------------------------------------------------------------
             |               Robust
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   .0244648   .0085564     2.86   0.004     .0076788    .0412508
    doveconc |    .083558   .0143891     5.81   0.000     .0553294    .1117865
      hawksq |       .075   .0147469     5.09   0.000     .0460695    .1039305
    hawkconc |   .0618182   .0145448     4.25   0.000     .0332841    .0903523
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq

 ( 1)  - dovesq + doveconc + hawksq - hawkconc = 0

------------------------------------------------------------------------------
dis~2_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0722749   .0266323     2.71   0.007     .0200276    .1245223
------------------------------------------------------------------------------

. 
. *Disposition -- Passed Manipulation Check / Full DV
. reg disapproval2 dovesq doveconc hawksq hawkconc if policy_manipcheck==1 & hawkdove_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,293
                                                F(4, 1289)        =     953.73
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7459
                                                Root MSE          =     1.3377

------------------------------------------------------------------------------
             |               Robust
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   1.908257   .0624135    30.57   0.000     1.785814      2.0307
    doveconc |   2.272237   .0765232    29.69   0.000     2.122114    2.422361
      hawksq |   2.590625   .0790168    32.79   0.000     2.435609    2.745641
    hawkconc |   2.349091   .0773003    30.39   0.000     2.197443    2.500739
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq

 ( 1)  - dovesq + doveconc + hawksq - hawkconc = 0

------------------------------------------------------------------------------
disapproval2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .6055144   .1482236     4.09   0.000     .3147285    .8963004
------------------------------------------------------------------------------

. 
. eststo clear

. 
. ********************************************************************************
. *                                        TABLE A-10: STUDY 2 7-POINT SCALE                                         
>         *
. ********************************************************************************
. 
. ***Main Effect of Gender -- Outcome 1, Full DV
. reg disapproval1 femsq femconc malesq maleconc, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(4, 2137)        =    2139.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8015
                                                Root MSE          =     1.5782

------------------------------------------------------------------------------
             |               Robust
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   2.839779   .0665919    42.64   0.000     2.709187    2.970371
     femconc |   3.533333   .0729851    48.41   0.000     3.390204    3.676463
      malesq |   2.792776   .0630097    44.32   0.000     2.669209    2.916342
    maleconc |   3.434211   .0696571    49.30   0.000     3.297608    3.570813
------------------------------------------------------------------------------

. lincom femconc-femsq

 ( 1)  - femsq + femconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .6935543   .0987993     7.02   0.000     .4998014    .8873072
------------------------------------------------------------------------------

. lincom maleconc-malesq

 ( 1)  - malesq + maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .6414349   .0939273     6.83   0.000     .4572365    .8256332
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0521195   .1363218     0.38   0.702    -.2152178    .3194567
------------------------------------------------------------------------------

. 
. *** Main Effect of Partisanship -- Outcome 1, Full DV
. reg disapproval1 demsq demconc repsq repconc, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(4, 2137)        =    2143.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8019
                                                Root MSE          =     1.5768

------------------------------------------------------------------------------
             |               Robust
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |     2.8431   .0665205    42.74   0.000     2.712648    2.973552
     demconc |     3.5878    .074216    48.34   0.000     3.442257    3.733343
       repsq |   2.790741   .0632763    44.10   0.000     2.666651     2.91483
     repconc |   3.378531   .0680408    49.65   0.000     3.245098    3.511964
------------------------------------------------------------------------------

. lincom demconc-demsq

 ( 1)  - demsq + demconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .7447002   .0996644     7.47   0.000     .5492508    .9401495
------------------------------------------------------------------------------

. lincom repconc-repsq

 ( 1)  - repsq + repconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5877903   .0929163     6.33   0.000     .4055744    .7700062
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1569098   .1362587     1.15   0.250    -.1103037    .4241234
------------------------------------------------------------------------------

. 
. *** Main Effect of Disposition -- Outcome 1, Full DV
. reg disapproval1 dovesq doveconc hawksq hawkconc, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(4, 2137)        =    2208.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8053
                                                Root MSE          =     1.5632

------------------------------------------------------------------------------
             |               Robust
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   2.514071   .0540747    46.49   0.000     2.408027    2.620116
    doveconc |   3.405607   .0723387    47.08   0.000     3.263746    3.547469
      hawksq |   3.117537    .071734    43.46   0.000     2.976862    3.258213
    hawkconc |   3.562384    .070292    50.68   0.000     3.424536    3.700232
------------------------------------------------------------------------------

. lincom doveconc-dovesq

 ( 1)  - dovesq + doveconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .8915362   .0903158     9.87   0.000     .7144201    1.068652
------------------------------------------------------------------------------

. lincom hawkconc-hawksq

 ( 1)  - hawksq + hawkconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4448463   .1004327     4.43   0.000     .2478902    .6418024
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq

 ( 1)  - dovesq + doveconc + hawksq - hawkconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4466899   .1350692     3.31   0.001     .1818091    .7115706
------------------------------------------------------------------------------

. 
. ********************************************************************************
. *                                        TABLE A-11: STUDY 2 MANIPULATION CHECK                                    
> *
. ********************************************************************************
. 
. ***Main Effect of Gender -- Outcome 1, Binary DV
. reg disapproval1_binary femsq femconc malesq maleconc if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,160
                                                F(4, 1156)        =      96.58
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2800
                                                Root MSE          =     .41386

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       femsq |   .1470588   .0202812     7.25   0.000     .1072667     .186851
     femconc |   .3547401   .0265032    13.38   0.000     .3027403    .4067399
      malesq |   .1240602   .0202471     6.13   0.000      .084335    .1637853
    maleconc |   .3103448   .0286859    10.82   0.000     .2540626     .366627
------------------------------------------------------------------------------

. lincom femconc-femsq

 ( 1)  - femsq + femconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2076812   .0333729     6.22   0.000      .142203    .2731594
------------------------------------------------------------------------------

. lincom maleconc-malesq

 ( 1)  - malesq + maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1862847   .0351116     5.31   0.000     .1173951    .2551743
------------------------------------------------------------------------------

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0213966   .0484414     0.44   0.659    -.0736464    .1164396
------------------------------------------------------------------------------

. 
. *** Main Effect of Partisanship -- Outcome 1, Binary DV
. reg disapproval1_binary demsq demconc repsq repconc if policy_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,529
                                                F(4, 1525)        =     121.95
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2731
                                                Root MSE          =     .40845

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       demsq |   .1270718   .0175278     7.25   0.000     .0926906     .161453
     demconc |   .3598972   .0243673    14.77   0.000     .3121001    .4076942
       repsq |   .1338384   .0171321     7.81   0.000     .1002334    .1674434
     repconc |   .2905759   .0232605    12.49   0.000     .2449499     .336202
------------------------------------------------------------------------------

. lincom demconc-demsq

 ( 1)  - demsq + demconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2328253   .0300165     7.76   0.000     .1739473    .2917034
------------------------------------------------------------------------------

. lincom repconc-repsq

 ( 1)  - repsq + repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1567375   .0288888     5.43   0.000     .1000716    .2134035
------------------------------------------------------------------------------

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0760878     .04166     1.83   0.068    -.0056291    .1578048
------------------------------------------------------------------------------

. 
. *** Main Effect of Disposition -- Outcome 1, Binary DV
. reg disapproval1_binary dovesq doveconc hawksq hawkconc if policy_manipcheck==1 & hawkdove_manipcheck==1, robust no
> const

Linear regression                               Number of obs     =      1,293
                                                F(4, 1289)        =     109.40
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2952
                                                Root MSE          =     .40972

------------------------------------------------------------------------------
             |               Robust
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dovesq |   .0458716   .0115871     3.96   0.000       .02314    .0686032
    doveconc |   .3261456   .0243767    13.38   0.000     .2783232    .3739679
      hawksq |     .24375   .0240382    10.14   0.000     .1965916    .2909084
    hawkconc |   .3381818   .0285727    11.84   0.000     .2821278    .3942359
------------------------------------------------------------------------------

. lincom doveconc-dovesq

 ( 1)  - dovesq + doveconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .280274   .0269904    10.38   0.000      .227324     .333224
------------------------------------------------------------------------------

. lincom hawkconc-hawksq

 ( 1)  - hawksq + hawkconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0944318   .0373395     2.53   0.012      .021179    .1676846
------------------------------------------------------------------------------

. lincom doveconc-dovesq-hawkconc+hawksq

 ( 1)  - dovesq + doveconc + hawksq - hawkconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1858422    .046073     4.03   0.000     .0954559    .2762284
------------------------------------------------------------------------------

. 
. ********************************************************************************
. *                                                TABLE A-12: STUDY 2 WITH COVARIATES                               
>         *
. ********************************************************************************
. 
. eststo clear

. 
. *Model 1: Main Effect of Gender -- Outcome 1, Binary DV
. eststo: reg disapproval1_binary femsq femconc malesq maleconc democrat dove hostsexism benevsexism secordersexism h
> awkish female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust nocon
> st

Linear regression                               Number of obs     =      1,970
                                                F(18, 1952)       =      30.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2573
                                                Root MSE          =     .38864

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  femsq |   .2673783   .0762156     3.51   0.000     .1179058    .4168509
                femconc |    .434615   .0757036     5.74   0.000     .2861467    .5830833
                 malesq |   .2400892   .0763385     3.15   0.002     .0903757    .3898027
               maleconc |   .3863458   .0737726     5.24   0.000     .2416643    .5310272
               democrat |    .024706   .0176278     1.40   0.161    -.0098652    .0592773
                   dove |  -.0767599    .017592    -4.36   0.000     -.111261   -.0422588
             hostsexism |  -.0280594   .0106255    -2.64   0.008     -.048898   -.0072208
            benevsexism |  -.0387887   .0080432    -4.82   0.000    -.0545629   -.0230145
         secordersexism |   .0097033   .0083131     1.17   0.243    -.0066002    .0260069
                hawkish |   .0002135   .0117967     0.02   0.986    -.0229219    .0233489
      female_respondent |   .0048965   .0185002     0.26   0.791    -.0313857    .0411788
political_identfication |   .0099647   .0042297     2.36   0.019     .0016696    .0182599
              education |  -.0016419   .0046243    -0.36   0.723    -.0107111    .0074272
                    hhi |   9.76e-06   .0000123     0.79   0.428    -.0000144    .0000339
                    age |   .0011179   .0005656     1.98   0.048     8.62e-06    .0022272
                  white |   .0072232   .0212363     0.34   0.734    -.0344251    .0488715
            SexismOrder |  -.0227897   .0176153    -1.29   0.196    -.0573364     .011757
       nonwhite_placebo |  -.0001026   .0210293    -0.00   0.996    -.0413449    .0411396
-----------------------------------------------------------------------------------------
(est1 stored)

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0209801   .0351344     0.60   0.550    -.0479247     .089885
------------------------------------------------------------------------------

.         
. *Model 2: Main Effect of Gender -- Outcome 1, Full DV
. eststo: reg disapproval1 femsq femconc malesq maleconc democrat dove hostsexism benevsexism secordersexism hawkish 
> female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(18, 1952)       =     459.83
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8103
                                                Root MSE          =     1.5433

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  femsq |   3.945938   .3101553    12.72   0.000     3.337668    4.554209
                femconc |   4.645454   .3086531    15.05   0.000      4.04013    5.250779
                 malesq |   3.873158   .3101113    12.49   0.000     3.264974    4.481342
               maleconc |    4.54945   .3019545    15.07   0.000     3.957262    5.141637
               democrat |   .1472438   .0700085     2.10   0.036     .0099446     .284543
                   dove |  -.4280089   .0699206    -6.12   0.000    -.5651359    -.290882
             hostsexism |   -.048204   .0450491    -1.07   0.285    -.1365534    .0401455
            benevsexism |  -.2140686   .0325612    -6.57   0.000    -.2779269   -.1502103
         secordersexism |  -.0022219   .0362883    -0.06   0.951    -.0733897     .068946
                hawkish |  -.1094876   .0510542    -2.14   0.032     -.209614   -.0093612
      female_respondent |   .2621605   .0737347     3.56   0.000     .1175535    .4067674
political_identfication |   .0249439   .0177641     1.40   0.160    -.0098946    .0597825
              education |  -.0434846   .0186843    -2.33   0.020    -.0801279   -.0068414
                    hhi |   -.000033    .000049    -0.67   0.501    -.0001291    .0000631
                    age |    .006344   .0022311     2.84   0.005     .0019683    .0107196
                  white |  -.0706962   .0850011    -0.83   0.406    -.2373987    .0960063
            SexismOrder |  -.0481593   .0700156    -0.69   0.492    -.1854725    .0891538
       nonwhite_placebo |   .0844317    .085346     0.99   0.323    -.0829472    .2518105
-----------------------------------------------------------------------------------------
(est2 stored)

. lincom femconc-femsq-maleconc+malesq

 ( 1)  - femsq + femconc + malesq - maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0232243   .1392201     0.17   0.868    -.2498113      .29626
------------------------------------------------------------------------------

. 
. *Model 3: Main Effect of Partisanship -- Outcome 1, Binary DV
. eststo: reg disapproval1_binary demsq demconc repsq repconc female dove hostsexism benevsexism secordersexism hawki
> sh female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(18, 1952)       =      30.06
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2580
                                                Root MSE          =     .38846

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  demsq |   .2451237    .075137     3.26   0.001     .0977665    .3924809
                demconc |   .4275937   .0738028     5.79   0.000     .2828531    .5723343
                  repsq |   .2463709   .0758764     3.25   0.001     .0975636    .3951781
                repconc |   .3772378   .0742575     5.08   0.000     .2316054    .5228702
                 female |   .0379911   .0175342     2.17   0.030     .0036034    .0723788
                   dove |  -.0764113   .0175873    -4.34   0.000    -.1109032   -.0419194
             hostsexism |  -.0280102   .0106081    -2.64   0.008    -.0488147   -.0072057
            benevsexism |  -.0388869   .0080052    -4.86   0.000    -.0545866   -.0231872
         secordersexism |   .0101624   .0082968     1.22   0.221    -.0061091     .026434
                hawkish |  -.0002465   .0117832    -0.02   0.983    -.0233555    .0228625
      female_respondent |   .0048105   .0184886     0.26   0.795     -.031449    .0410701
political_identfication |    .010135   .0042337     2.39   0.017     .0018319     .018438
              education |  -.0016732   .0046303    -0.36   0.718    -.0107541    .0074077
                    hhi |   .0000103   .0000122     0.85   0.398    -.0000137    .0000343
                    age |   .0011289   .0005647     2.00   0.046     .0000215    .0022363
                  white |     .00725   .0212318     0.34   0.733    -.0343893    .0488893
            SexismOrder |  -.0223075   .0175902    -1.27   0.205    -.0568051    .0121901
       nonwhite_placebo |  -.0004708   .0209827    -0.02   0.982    -.0416216      .04068
-----------------------------------------------------------------------------------------
(est3 stored)

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .051603   .0349559     1.48   0.140    -.0169518    .1201579
------------------------------------------------------------------------------

.         
. *Model 4: Main Effect of Partisanship -- Outcome 1, Full DV
. eststo: reg disapproval1 demsq demconc repsq repconc female dove hostsexism benevsexism secordersexism hawkish fema
> le_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(18, 1952)       =     460.28
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8104
                                                Root MSE          =      1.543

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                  demsq |   3.980449   .3083989    12.91   0.000     3.375623    4.585274
                demconc |   4.732942   .3011469    15.72   0.000     4.142339    5.323546
                  repsq |   3.898437   .3066603    12.71   0.000     3.297021    4.499853
                repconc |   4.521063   .3048247    14.83   0.000     3.923247     5.11888
                 female |   .0849068   .0695539     1.22   0.222    -.0515009    .2213144
                   dove |  -.4270793   .0699391    -6.11   0.000    -.5642426    -.289916
             hostsexism |  -.0483388   .0450074    -1.07   0.283    -.1366065    .0399289
            benevsexism |  -.2142028   .0325038    -6.59   0.000    -.2779486   -.1504569
         secordersexism |   -.001276   .0362731    -0.04   0.972    -.0724141    .0698621
                hawkish |  -.1102285   .0509773    -2.16   0.031    -.2102042   -.0102528
      female_respondent |   .2618151    .073735     3.55   0.000     .1172074    .4064228
political_identfication |   .0253557   .0177685     1.43   0.154    -.0094914    .0602029
              education |  -.0436745   .0187245    -2.33   0.020    -.0803966   -.0069523
                    hhi |  -.0000317   .0000489    -0.65   0.517    -.0001275    .0000642
                    age |    .006351   .0022301     2.85   0.004     .0019774    .0107245
                  white |  -.0709939   .0849617    -0.84   0.403    -.2376191    .0956313
            SexismOrder |   -.047512    .069992    -0.68   0.497    -.1847788    .0897548
       nonwhite_placebo |   .0828212   .0852955     0.97   0.332    -.0844587     .250101
-----------------------------------------------------------------------------------------
(est4 stored)

. lincom demconc-demsq-repconc+repsq

 ( 1)  - demsq + demconc + repsq - repconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1298672   .1389381     0.93   0.350    -.1426154    .4023498
------------------------------------------------------------------------------

. 
. *Model 5: Main Effect of Disposition -- Outcome 1, Binary DV
. eststo: reg disapproval1_binary hawksq hawkconc dovesq doveconc female democrat hostsexism benevsexism secordersexi
> sm hawkish female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust n
> oconst

Linear regression                               Number of obs     =      1,970
                                                F(18, 1952)       =      30.31
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2634
                                                Root MSE          =     .38706

-----------------------------------------------------------------------------------------
                        |               Robust
    disapproval1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                 hawksq |   .2736219   .0758901     3.61   0.000     .1247878     .422456
               hawkconc |   .3596554   .0731798     4.91   0.000     .2161366    .5031742
                 dovesq |   .1253379   .0710922     1.76   0.078    -.0140866    .2647625
               doveconc |   .3530939   .0718034     4.92   0.000     .2122745    .4939133
                 female |   .0378852   .0174808     2.17   0.030     .0036023    .0721682
               democrat |   .0253939    .017556     1.45   0.148    -.0090367    .0598244
             hostsexism |  -.0266027   .0105772    -2.52   0.012    -.0473466   -.0058589
            benevsexism |   -.040041   .0080239    -4.99   0.000    -.0557773   -.0243047
         secordersexism |   .0102051    .008282     1.23   0.218    -.0060375    .0264476
                hawkish |  -.0017404   .0117502    -0.15   0.882    -.0247847    .0213038
      female_respondent |   .0046273   .0184051     0.25   0.802    -.0314685     .040723
political_identfication |   .0097802   .0042159     2.32   0.020      .001512    .0180483
              education |  -.0014759   .0046007    -0.32   0.748    -.0104987    .0075469
                    hhi |   8.73e-06   .0000124     0.70   0.482    -.0000156    .0000331
                    age |   .0011883   .0005629     2.11   0.035     .0000844    .0022922
                  white |   .0057787   .0211681     0.27   0.785    -.0357357    .0472932
            SexismOrder |  -.0265667   .0176243    -1.51   0.132    -.0611312    .0079978
       nonwhite_placebo |   .0011771   .0208689     0.06   0.955    -.0397505    .0421047
-----------------------------------------------------------------------------------------
(est5 stored)

. lincom doveconc-dovesq-hawkconc+hawksq

 ( 1)  hawksq - hawkconc - dovesq + doveconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1417224   .0351372     4.03   0.000     .0728121    .2106328
------------------------------------------------------------------------------

.         
. *Model 6: Main Effect of Disposition -- Outcome 1, Full DV
. eststo: reg disapproval1 hawksq hawkconc dovesq doveconc female democrat hostsexism benevsexism secordersexism hawk
> ish female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(18, 1952)       =     467.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8119
                                                Root MSE          =     1.5371

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                 hawksq |   4.023487   .3071904    13.10   0.000     3.421032    4.625943
               hawkconc |   4.433931   .3005369    14.75   0.000     3.844524    5.023338
                 dovesq |   3.315237    .294897    11.24   0.000     2.736891    3.893583
               doveconc |   4.281176   .2958899    14.47   0.000     3.700883    4.861469
                 female |   .0847703   .0693286     1.22   0.222    -.0511956    .2207362
               democrat |   .1501058   .0697572     2.15   0.032     .0132993    .2869123
             hostsexism |  -.0430103   .0448727    -0.96   0.338    -.1310138    .0449931
            benevsexism |  -.2187519   .0325393    -6.72   0.000    -.2825673   -.1549365
         secordersexism |  -.0006734   .0362522    -0.02   0.985    -.0717705    .0704238
                hawkish |  -.1163149   .0507866    -2.29   0.022    -.2159166   -.0167131
      female_respondent |    .260848   .0733838     3.55   0.000     .1169292    .4047667
political_identfication |   .0241875   .0177003     1.37   0.172     -.010526    .0589009
              education |  -.0430557   .0186008    -2.31   0.021    -.0795352   -.0065762
                    hhi |  -.0000373   .0000494    -0.76   0.450    -.0001341    .0000595
                    age |   .0065785   .0022198     2.96   0.003     .0022251     .010932
                  white |  -.0770865    .084629    -0.91   0.362    -.2430593    .0888863
            SexismOrder |  -.0640933   .0699726    -0.92   0.360    -.2013222    .0731356
       nonwhite_placebo |   .0880834   .0849454     1.04   0.300    -.0785099    .2546766
-----------------------------------------------------------------------------------------
(est6 stored)

. lincom doveconc-dovesq-hawkconc+hawksq

 ( 1)  hawksq - hawkconc - dovesq + doveconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5554955   .1393167     3.99   0.000     .2822704    .8287206
------------------------------------------------------------------------------

. 
. esttab using "${results}/table_a12.tex", cells(b(fmt(3)) ci(fmt(3) par)) noeqlines eqlabels(none) nogaps se varlabe
> ls(demsq "Democratic x Status Quo" demconc "Democratic x Conciliatory" repsq "Republican x Status Quo" repconc "Rep
> ublican x Conciliatory" femsq "Female x Status Quo" femconc "Female x Conciliatory" malesq "Male x Status Quo" male
> conc "Male x Conciliatory" dovesq "Dovish x Status Quo" doveconc "Dovish x Conciliatory" hawksq "Hawkish x Status Q
> uo" hawkconc "Hawkish x Conciliatory" democrat "Democratic President" female "Female President" dove "Dovish Presid
> ent") keep(malesq maleconc femsq femconc repsq repconc demsq demconc hawksq hawkconc dovesq doveconc female democra
> t dove) order(malesq maleconc femsq femconc repsq repconc demsq demconc hawksq hawkconc dovesq doveconc female demo
> crat dove) label star(* 0.10 ** 0.05 *** .01) nonotes mtitle("Disapproval (Binary)" "Disapproval (7-Point)" "Disapp
> roval (Binary)" "Disapproval (7-Point)" "Disapproval (Binary)" "Disapproval (7-Point)") b(3) se(3) replace
(note: file /Users/cb2257/Desktop/ISQ Replication/results/table_a12.tex not found)
(output written to ~/Desktop/ISQ Replication/results/table_a12.tex)

. eststo clear

. 
. ********************************************************************************
. *                                        TABLE A-13: STUDY 2 GENDER X DEM PRESIDENT                                
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Binary DV, Full Sample
. eststo: reg disapproval1_binary 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.
> maleconc 1.maleconc#democrat, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(8, 2133)        =      71.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2352
                                                Root MSE          =     .39356

-----------------------------------------------------------------------------------
                  |               Robust
disapproval1_bi~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |   .1098901   .0189641     5.79   0.000        .0727    .1470802
                  |
   femsq#democrat |
             1 1  |   .0456654     .02912     1.57   0.117    -.0114411     .102772
                  |
        1.femconc |   .2781955   .0275269    10.11   0.000     .2242132    .3321778
                  |
 femconc#democrat |
             1 1  |   .0429724   .0394513     1.09   0.276    -.0343946    .1203394
                  |
         1.malesq |   .1423221   .0214218     6.64   0.000     .1003123    .1843319
                  |
  malesq#democrat |
             1 1  |   -.053519   .0277936    -1.93   0.054    -.1080244    .0009864
                  |
       1.maleconc |   .2377358   .0261993     9.07   0.000      .186357    .2891147
                  |
maleconc#democrat |
             1 1  |   .0394177   .0379415     1.04   0.299    -.0349884    .1138238
-----------------------------------------------------------------------------------
(est1 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0227381   .0485155    -0.47   0.639    -.1178807    .0724045
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0728916   .0475675     1.53   0.126    -.0203918    .1661751
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0956298   .0679442    -1.41   0.159    -.2288736    .0376141
------------------------------------------------------------------------------

. 
. ***Model 2: 7-Point DV, Full Sample
. eststo: reg disapproval1 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.malecon
> c 1.maleconc#democrat, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(8, 2133)        =    1075.23
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8021
                                                Root MSE          =     1.5776

-----------------------------------------------------------------------------------
                  |               Robust
     disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |   2.776557   .0886385    31.32   0.000      2.60273    2.950384
                  |
   femsq#democrat |
             1 1  |   .1271469   .1332795     0.95   0.340    -.1342244    .3885183
                  |
        1.femconc |   3.413534   .0979645    34.84   0.000     3.221418     3.60565
                  |
 femconc#democrat |
             1 1  |   .2361012   .1455341     1.62   0.105    -.0493023    .5215047
                  |
         1.malesq |   2.805243    .090514    30.99   0.000     2.627739    2.982748
                  |
  malesq#democrat |
             1 1  |  -.0253207   .1260584    -0.20   0.841    -.2725308    .2218895
                  |
       1.maleconc |   3.343396   .0945731    35.35   0.000     3.157931    3.528861
                  |
maleconc#democrat |
             1 1  |   .1809483    .139182     1.30   0.194    -.0919982    .4538949
-----------------------------------------------------------------------------------
(est2 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0015095   .1990358     0.01   0.994     -.388815     .391834
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0988243   .1859857     0.53   0.595     -.265908    .4635565
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0973147   .2724077    -0.36   0.721    -.6315271    .4368976
------------------------------------------------------------------------------

. 
. ***Model 3: Binary DV, Attentive Sample
. eststo: reg disapproval1_binary 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.
> maleconc 1.maleconc#democrat if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,160
                                                F(8, 1152)        =      48.52
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2850
                                                Root MSE          =     .41314

-----------------------------------------------------------------------------------
                  |               Robust
disapproval1_bi~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |      .1125    .025067     4.49   0.000     .0633178    .1616822
                  |
   femsq#democrat |
             1 1  |   .0724315   .0408404     1.77   0.076    -.0076983    .1525614
                  |
        1.femconc |   .3184713   .0373104     8.54   0.000     .2452673    .3916753
                  |
 femconc#democrat |
             1 1  |    .069764   .0529044     1.32   0.188    -.0340359    .1735638
                  |
         1.malesq |   .1589404   .0298569     5.32   0.000     .1003604    .2175204
                  |
  malesq#democrat |
             1 1  |  -.0806795   .0390264    -2.07   0.039    -.1572504   -.0041087
                  |
       1.maleconc |   .2877698   .0385326     7.47   0.000     .2121679    .3633717
                  |
maleconc#democrat |
             1 1  |   .0482958   .0576746     0.84   0.403    -.0648632    .1614548
-----------------------------------------------------------------------------------
(est3 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0545009     .07014    -0.78   0.437    -.1921173    .0831155
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .077142    .066307     1.16   0.245    -.0529541     .207238
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.1316429   .0965206    -1.36   0.173    -.3210188    .0577331
------------------------------------------------------------------------------

. 
. ***Model 4: 7-Point DV, Attentive Sample
. eststo: reg disapproval1 1.femsq 1.femsq#democrat 1.femconc 1.femconc#democrat 1.malesq 1.malesq#democrat 1.malecon
> c 1.maleconc#democrat if policy_manipcheck==1 & name_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,160
                                                F(8, 1152)        =     633.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8153
                                                Root MSE          =     1.5646

-----------------------------------------------------------------------------------
                  |               Robust
     disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
          1.femsq |    2.68125   .1116187    24.02   0.000     2.462251    2.900249
                  |
   femsq#democrat |
             1 1  |   .2571062   .1789879     1.44   0.151    -.0940726    .6082849
                  |
        1.femconc |   3.630573   .1210297    30.00   0.000      3.39311    3.868037
                  |
 femconc#democrat |
             1 1  |   .2811915   .1813679     1.55   0.121     -.074657    .6370399
                  |
         1.malesq |   2.721854   .1264942    21.52   0.000     2.473669    2.970039
                  |
  malesq#democrat |
             1 1  |  -.0522891   .1770271    -0.30   0.768    -.3996207    .2950425
                  |
       1.maleconc |    3.52518    .132066    26.69   0.000     3.266063    3.784297
                  |
maleconc#democrat |
             1 1  |   .2043283   .1956617     1.04   0.297    -.1795648    .5882215
-----------------------------------------------------------------------------------
(est4 stored)

. 
. *Gendered Peace Premium (Democratic President)
. lincom (1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+1
> .malesq#1.democrat)

 ( 1)  - 1.femsq - 1.femsq#1.democrat + 1.femconc + 1.femconc#1.democrat + 1.malesq + 1.malesq#1.democrat -
       1.maleconc - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0865344   .2720366    -0.32   0.750    -.6202772    .4472083
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Democratic President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1459977   .2460673     0.59   0.553    -.3367927    .6287881
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.democrat)-(1.femsq+1.femsq#1.democrat)-(1.maleconc+1.maleconc#1.democrat)+(1.malesq+
> 1.malesq#1.democrat))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.democrat + 1.femconc#1.democrat + 1.malesq#1.democrat - 1.maleconc#1.democrat = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.2325321   .3668147    -0.63   0.526     -.952232    .4871677
------------------------------------------------------------------------------

. 
. eststo clear

. 
. ********************************************************************************
. *                                TABLE A-14: STUDY 2 GENDER X DISP PRESIDENT                               *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Binary DV, Full Sample
. eststo: reg disapproval1_binary 1.femsq 1.femsq#hawk 1.femconc 1.femconc#hawk 1.malesq 1.malesq#hawk 1.maleconc 1.m
> aleconc#hawk, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(8, 2133)        =      71.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2451
                                                Root MSE          =     .39103

-------------------------------------------------------------------------------
              |               Robust
disa~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
      1.femsq |   .0555556   .0139664     3.98   0.000     .0281665    .0829446
              |
   femsq#hawk |
         1 1  |   .1532357   .0283275     5.41   0.000     .0976832    .2087881
              |
    1.femconc |   .2862454   .0276109    10.37   0.000     .2320983    .3403924
              |
 femconc#hawk |
         1 1  |   .0274078   .0394932     0.69   0.488    -.0500414     .104857
              |
     1.malesq |   .0532319   .0138689     3.84   0.000     .0260339      .08043
              |
  malesq#hawk |
         1 1  |   .1254753   .0274318     4.57   0.000     .0716794    .1792712
              |
   1.maleconc |   .2593985   .0269245     9.63   0.000     .2065974    .3121996
              |
maleconc#hawk |
         1 1  |  -.0037594   .0379866    -0.10   0.921     -.078254    .0707352
-------------------------------------------------------------------------------
(est1 stored)

. 
. *Gendered Peace Premium (Hawkish President)
. lincom (1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.ha
> wk)

 ( 1)  - 1.femsq - 1.femsq#1.hawk + 1.femconc + 1.femconc#1.hawk + 1.malesq + 1.malesq#1.hawk - 1.maleconc -
       1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0279301   .0517972     0.54   0.590    -.0736482    .1295083
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Dovish President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0245232   .0432978     0.57   0.571     -.060387    .1094335
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.h
> awk))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hawk + 1.femconc#1.hawk + 1.malesq#1.hawk - 1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0034068   .0675103     0.05   0.960    -.1289861    .1357998
------------------------------------------------------------------------------

. 
. ***Model 2: 7-Point DV, Full Sample
. eststo: reg disapproval1 1.femsq 1.femsq#hawk 1.femconc 1.femconc#hawk 1.malesq 1.malesq#hawk 1.maleconc 1.maleconc
> #hawk, robust noconst

Linear regression                               Number of obs     =      2,141
                                                F(8, 2133)        =    1106.20
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8054
                                                Root MSE          =     1.5641

-------------------------------------------------------------------------------
              |               Robust
 disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
      1.femsq |   2.525926   .0781281    32.33   0.000     2.372711    2.679141
              |
   femsq#hawk |
         1 1  |   .6242572   .1303742     4.79   0.000     .3685835     .879931
              |
    1.femconc |   3.431227   .1034816    33.16   0.000     3.228291    3.634162
              |
 femconc#hawk |
         1 1  |   .2034596   .1458461     1.40   0.163    -.0825559    .4894751
              |
     1.malesq |   2.501901   .0748186    33.44   0.000     2.355176    2.648626
              |
  malesq#hawk |
         1 1  |    .581749    .123551     4.71   0.000     .3394561     .824042
              |
   1.maleconc |   3.379699   .1012501    33.38   0.000      3.18114    3.578258
              |
maleconc#hawk |
         1 1  |   .1090226   .1393643     0.78   0.434    -.1642815    .3823266
-------------------------------------------------------------------------------
(est2 stored)

. 
. *Gendered Peace Premium (Hawkish President)
. lincom (1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.ha
> wk)

 ( 1)  - 1.femsq - 1.femsq#1.hawk + 1.femconc + 1.femconc#1.hawk + 1.malesq + 1.malesq#1.hawk - 1.maleconc -
       1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0794316   .2007335     0.40   0.692    -.3142222    .4730854
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Dovish President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0275027   .1807258     0.15   0.879    -.3269145      .38192
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.h
> awk))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hawk + 1.femconc#1.hawk + 1.malesq#1.hawk - 1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0519288   .2701032     0.19   0.848    -.4777644    .5816221
------------------------------------------------------------------------------

. 
. ***Model 3: Binary DV, Attentive Sample
. eststo: reg disapproval1_binary 1.femsq 1.femsq#hawk 1.femconc 1.femconc#hawk 1.malesq 1.malesq#hawk 1.maleconc 1.m
> aleconc#hawk if policy_manipcheck==1 & name_manipcheck==1 & hawkdove_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,024
                                                F(8, 1016)        =      43.67
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2986
                                                Root MSE          =     .41126

-------------------------------------------------------------------------------
              |               Robust
disa~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
      1.femsq |   .0425532   .0170654     2.49   0.013     .0090657    .0760407
              |
   femsq#hawk |
         1 1  |   .2330374   .0433079     5.38   0.000     .1480541    .3180206
              |
    1.femconc |    .343949     .03806     9.04   0.000     .2692638    .4186343
              |
 femconc#hawk |
         1 1  |   .0022048   .0565976     0.04   0.969    -.1088567    .1132663
              |
     1.malesq |   .0495868    .019813     2.50   0.012     .0107078    .0884658
              |
  malesq#hawk |
         1 1  |   .1754132   .0430943     4.07   0.000     .0908492    .2599773
              |
   1.maleconc |   .3157895   .0404642     7.80   0.000     .2363865    .3951924
              |
maleconc#hawk |
         1 1  |   7.81e-17   .0626869     0.00   1.000    -.1230106    .1230106
-------------------------------------------------------------------------------
(est3 stored)

. 
. *Gendered Peace Premium (Hawkish President)
. lincom (1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.ha
> wk)

 ( 1)  - 1.femsq - 1.femsq#1.hawk + 1.femconc + 1.femconc#1.hawk + 1.malesq + 1.malesq#1.hawk - 1.maleconc -
       1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0202262   .0842373    -0.24   0.810    -.1855252    .1450729
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Dovish President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0351932   .0613979     0.57   0.567     -.085288    .1556743
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.h
> awk))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hawk + 1.femconc#1.hawk + 1.malesq#1.hawk - 1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
dis~1_binary |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0554193   .1042383    -0.53   0.595    -.2599664    .1491277
------------------------------------------------------------------------------

. 
. ***Model 4: 7-Point DV, Attentive Sample
. eststo: reg disapproval1 1.femsq 1.femsq#hawk 1.femconc 1.femconc#hawk 1.malesq 1.malesq#hawk 1.maleconc 1.maleconc
> #hawk if policy_manipcheck==1 & name_manipcheck==1 & hawkdove_manipcheck==1, robust noconst

Linear regression                               Number of obs     =      1,024
                                                F(8, 1016)        =     601.16
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8265
                                                Root MSE          =     1.5199

-------------------------------------------------------------------------------
              |               Robust
 disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
      1.femsq |   2.333333    .097971    23.82   0.000     2.141085    2.525582
              |
   femsq#hawk |
         1 1  |   1.060367   .1816277     5.84   0.000     .7039591    1.416776
              |
    1.femconc |    3.66879   .1342496    27.33   0.000     3.405352    3.932228
              |
 femconc#hawk |
         1 1  |   .2158256   .1925185     1.12   0.263    -.1619538     .593605
              |
     1.malesq |   2.214876    .099706    22.21   0.000     2.019223    2.410529
              |
  malesq#hawk |
         1 1  |   1.051791   .1789447     5.88   0.000     .7006472    1.402934
              |
   1.maleconc |   3.518797   .1434588    24.53   0.000     3.237288    3.800306
              |
maleconc#hawk |
         1 1  |   .2601504   .2077953     1.25   0.211    -.1476068    .6679075
-------------------------------------------------------------------------------
(est4 stored)

. 
. *Gendered Peace Premium (Hawkish President)
. lincom (1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.ha
> wk)

 ( 1)  - 1.femsq - 1.femsq#1.hawk + 1.femconc + 1.femconc#1.hawk + 1.malesq + 1.malesq#1.hawk - 1.maleconc -
       1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0213661   .2951425    -0.07   0.942    -.6005248    .5577926
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Dovish President)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0315355   .2411286     0.13   0.896    -.4416314    .5047025
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hawk)-(1.femsq+1.femsq#1.hawk)-(1.maleconc+1.maleconc#1.hawk)+(1.malesq+1.malesq#1.h
> awk))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hawk + 1.femconc#1.hawk + 1.malesq#1.hawk - 1.maleconc#1.hawk = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0529016   .3811195    -0.14   0.890    -.8007731    .6949699
------------------------------------------------------------------------------

. 
. eststo clear

. 
. 
. ********************************************************************************
. *                                TABLE A-15: STUDY 2 DISPOSITION MEDIATION                                         
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***** COMPETENCE ***** 
. 
. ***Hawk
. medeff (regress beststrategy1 conciliatory female democrat hostsexism benevsexism secordersexism hawkish female_res
> pondent political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 beststr
> ategy1 conciliatory female democrat hostsexism benevsexism hawkish female_respondent political_identfication educat
> ion hhi age white SexismOrder nonwhite_placebo) if hawk==1, mediate(beststrategy1) treat(conciliatory) sims(2000) s
> eed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       986
-------------+----------------------------------   F(15, 970)      =      8.06
       Model |  316.452792        15  21.0968528   Prob > F        =    0.0000
    Residual |  2540.50461       970  2.61907692   R-squared       =    0.1108
-------------+----------------------------------   Adj R-squared   =    0.0970
       Total |   2856.9574       985  2.90046437   Root MSE        =    1.6184

-----------------------------------------------------------------------------------------
          beststrategy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -.3024257   .1039089    -2.91   0.004    -.5063379   -.0985135
                 female |  -.1931081   .1039666    -1.86   0.064    -.3971334    .0109173
               democrat |  -.0185178   .1038055    -0.18   0.858     -.222227    .1851913
             hostsexism |   .1166563   .0598267     1.95   0.051    -.0007483    .2340609
            benevsexism |   .1462497   .0451424     3.24   0.001     .0576616    .2348378
         secordersexism |   .0432222   .0486386     0.89   0.374    -.0522269    .1386713
                hawkish |   .3941566    .064555     6.11   0.000     .2674731    .5208401
      female_respondent |  -.4244814   .1079239    -3.93   0.000    -.6362726   -.2126903
political_identfication |   .0258363   .0254627     1.01   0.311    -.0241321    .0758046
              education |   .0021929   .0278207     0.08   0.937    -.0524028    .0567886
                    hhi |  -.0000876   .0000815    -1.07   0.283    -.0002475    .0000724
                    age |  -.0022095   .0032951    -0.67   0.503    -.0086759    .0042569
                  white |  -.1673993   .1271734    -1.32   0.188     -.416966    .0821674
            SexismOrder |    -.03785   .1038334    -0.36   0.716     -.241614     .165914
       nonwhite_placebo |   .0438367   .1299693     0.34   0.736    -.2112167      .29889
                  _cons |    2.91193   .3918922     7.43   0.000     2.142876    3.680984
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       986
-------------+----------------------------------   F(15, 970)      =    136.62
       Model |  1872.98093        15  124.865396   Prob > F        =    0.0000
    Residual |   886.57282       970  .913992598   R-squared       =    0.6787
-------------+----------------------------------   Adj R-squared   =    0.6738
       Total |  2759.55375       985  2.80157741   Root MSE        =    .95603

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .1799818   .0615811     2.92   0.004     .0591343    .3008293
          beststrategy1 |  -.7736215   .0189598   -40.80   0.000    -.8108285   -.7364144
                 female |  -.0059847   .0615187    -0.10   0.923    -.1267099    .1147404
               democrat |   .0447243   .0613036     0.73   0.466    -.0755787    .1650274
             hostsexism |   -.022466   .0350979    -0.64   0.522    -.0913427    .0464106
            benevsexism |  -.0317632   .0259179    -1.23   0.221    -.0826248    .0190984
                hawkish |  -.1287436   .0388521    -3.31   0.001    -.2049874   -.0524998
      female_respondent |   .0698532   .0642599     1.09   0.277    -.0562513    .1959577
political_identfication |   .0038931   .0150401     0.26   0.796    -.0256217    .0334079
              education |  -.0135966   .0163968    -0.83   0.407    -.0457738    .0185806
                    hhi |  -.0000491   .0000482    -1.02   0.309    -.0001436    .0000454
                    age |   .0044751   .0019461     2.30   0.022     .0006561    .0082941
                  white |   -.076323   .0751534    -1.02   0.310     -.223805    .0711591
            SexismOrder |  -.0703855   .0613404    -1.15   0.251    -.1907607    .0499896
       nonwhite_placebo |  -.0201624     .07673    -0.26   0.793    -.1707384    .1304136
                  _cons |   7.266474   .2212422    32.84   0.000     6.832306    7.700643
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .2332597      .0729857      .3950224
        Direct Effect          |   .180604      .0604709      .3028847
        Total Effect           |  .4138637      .3752333       .454365
        % of Tot Eff mediated  |    .56457      .5133753      .6216393
------------------------------------------------------------------------------------

. 
. ***Doves        
. medeff (regress beststrategy1 conciliatory female democrat hostsexism benevsexism secordersexism hawkish female_res
> pondent political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 beststr
> ategy1 conciliatory female democrat hostsexism benevsexism hawkish female_respondent political_identfication educat
> ion hhi age white SexismOrder nonwhite_placebo) if dove==1, mediate(beststrategy1) treat(conciliatory) sims(2000) s
> eed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       984
-------------+----------------------------------   F(15, 968)      =     15.73
       Model |  509.684815        15  33.9789877   Prob > F        =    0.0000
    Residual |  2091.33551       968  2.16047057   R-squared       =    0.1960
-------------+----------------------------------   Adj R-squared   =    0.1835
       Total |  2601.02033       983  2.64600237   Root MSE        =    1.4699

-----------------------------------------------------------------------------------------
          beststrategy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -1.074867   .0943502   -11.39   0.000    -1.260021   -.8897123
                 female |   -.034407   .0944292    -0.36   0.716    -.2197165    .1509025
               democrat |  -.1644776   .0946196    -1.74   0.082    -.3501608    .0212055
             hostsexism |  -.0732643   .0556307    -1.32   0.188    -.1824349    .0359063
            benevsexism |   .3164766   .0436193     7.26   0.000     .2308772    .4020759
         secordersexism |   -.113325   .0466274    -2.43   0.015    -.2048275   -.0218226
                hawkish |  -.2599761   .0601957    -4.32   0.000    -.3781052    -.141847
      female_respondent |  -.0275998   .0969678    -0.28   0.776    -.2178912    .1626916
political_identfication |  -.0108941   .0237593    -0.46   0.647    -.0575199    .0357316
              education |   .0390219   .0249408     1.56   0.118    -.0099223    .0879661
                    hhi |   .0000382   .0000682     0.56   0.576    -.0000957    .0001721
                    age |  -.0074164   .0029957    -2.48   0.013    -.0132953   -.0015375
                  white |   .1193136   .1165389     1.02   0.306    -.1093844    .3480115
            SexismOrder |   .1076199    .095126     1.13   0.258    -.0790571    .2942969
       nonwhite_placebo |  -.2612762   .1070247    -2.44   0.015    -.4713034   -.0512491
                  _cons |   6.055004   .3712169    16.31   0.000     5.326521    6.783486
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       984
-------------+----------------------------------   F(15, 968)      =    166.07
       Model |  1715.49074        15   114.36605   Prob > F        =    0.0000
    Residual |  666.639339       968  .688677003   R-squared       =    0.7201
-------------+----------------------------------   Adj R-squared   =    0.7158
       Total |  2382.13008       983  2.42332663   Root MSE        =    .82987

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .1206775    .056727     2.13   0.034     .0093555    .2319995
          beststrategy1 |  -.7725646   .0180915   -42.70   0.000    -.8080677   -.7370615
                 female |   -.005662   .0532949    -0.11   0.915    -.1102488    .0989248
               democrat |   .0690519   .0534917     1.29   0.197    -.0359211    .1740249
             hostsexism |   .0129554   .0309355     0.42   0.675     -.047753    .0736637
            benevsexism |  -.0523264    .023611    -2.22   0.027    -.0986611   -.0059918
                hawkish |   .0270541   .0342821     0.79   0.430    -.0402216    .0943299
      female_respondent |   .1205735   .0546335     2.21   0.028     .0133597    .2277873
political_identfication |   .0353993   .0134127     2.64   0.008     .0090779    .0617206
              education |  -.0212658   .0140725    -1.51   0.131    -.0488819    .0063502
                    hhi |  -.0000584   .0000385    -1.52   0.129     -.000134    .0000171
                    age |   .0018437   .0016928     1.09   0.276    -.0014781    .0051656
                  white |  -.1004428   .0655995    -1.53   0.126    -.2291764    .0282909
            SexismOrder |  -.0152079   .0537358    -0.28   0.777      -.12066    .0902442
       nonwhite_placebo |   .0723108   .0605196     1.19   0.232    -.0464539    .1910755
                  _cons |   6.547188   .2164371    30.25   0.000     6.122448    6.971928
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .8300722      .6683008      .9920884
        Direct Effect          |  .1212506      .0105871      .2338926
        Total Effect           |  .9513228      .8959525      1.011397
        % of Tot Eff mediated  |  .8736748      .8207182      .9264689
------------------------------------------------------------------------------------

. 
. ***** MODERATION ***** 
. 
. ***Hawk
. medeff (regress moderate conciliatory female democrat hostsexism benevsexism secordersexism hawkish female_responde
> nt political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 moderate con
> ciliatory female democrat hostsexism benevsexism hawkish female_respondent political_identfication education hhi ag
> e white SexismOrder nonwhite_placebo) if hawk==1, mediate(moderate) treat(conciliatory) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       986
-------------+----------------------------------   F(15, 970)      =      4.13
       Model |  6.82028227        15  .454685485   Prob > F        =    0.0000
    Residual |  106.775052       970  .110077374   R-squared       =    0.0600
-------------+----------------------------------   Adj R-squared   =    0.0455
       Total |  113.595335       985  .115325213   Root MSE        =    .33178

-----------------------------------------------------------------------------------------
               moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -.0152136   .0213024    -0.71   0.475    -.0570176    .0265905
                 female |    .033566   .0213142     1.57   0.116    -.0082612    .0753932
               democrat |   -.051121   .0212812    -2.40   0.016    -.0928834   -.0093586
             hostsexism |  -.0316665   .0122651    -2.58   0.010    -.0557356   -.0075974
            benevsexism |  -.0477613   .0092546    -5.16   0.000    -.0659227   -.0295999
         secordersexism |  -.0045925   .0099714    -0.46   0.645    -.0241605    .0149755
                hawkish |   .0243587   .0132344     1.84   0.066    -.0016127    .0503301
      female_respondent |  -.0153242   .0221255    -0.69   0.489    -.0587435    .0280951
political_identfication |   .0094322   .0052201     1.81   0.071    -.0008118    .0196762
              education |  -.0028473   .0057035    -0.50   0.618      -.01404    .0083454
                    hhi |    .000032   .0000167     1.92   0.056    -7.67e-07    .0000648
                    age |   .0016062   .0006755     2.38   0.018     .0002805    .0029319
                  white |  -.0093064   .0260718    -0.36   0.721      -.06047    .0418573
            SexismOrder |  -.0079414   .0212869    -0.37   0.709     -.049715    .0338323
       nonwhite_placebo |  -.0190068    .026645    -0.71   0.476    -.0712953    .0332817
                  _cons |    .285788   .0803418     3.56   0.000     .1281242    .4434517
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       986
-------------+----------------------------------   F(15, 970)      =     11.50
       Model |  416.799746        15  27.7866498   Prob > F        =    0.0000
    Residual |  2342.75401       970  2.41521032   R-squared       =    0.1510
-------------+----------------------------------   Adj R-squared   =    0.1379
       Total |  2759.55375       985  2.80157741   Root MSE        =    1.5541

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .3984623   .0997093     4.00   0.000     .2027915    .5941331
               moderate |  -.7832791   .1503817    -5.21   0.000     -1.07839   -.4881681
                 female |    .168577   .0999547     1.69   0.092    -.0275754    .3647294
               democrat |   .0170258   .0999512     0.17   0.865    -.1791196    .2131713
             hostsexism |   -.131538   .0571435    -2.30   0.022    -.2436772   -.0193988
            benevsexism |  -.1912682    .042494    -4.50   0.000     -.274659   -.1078774
                hawkish |  -.4159523   .0620746    -6.70   0.000    -.5377682   -.2941364
      female_respondent |   .3859614   .1036636     3.72   0.000     .1825307    .5893922
political_identfication |  -.0080249   .0244784    -0.33   0.743    -.0560616    .0400119
              education |  -.0189675   .0266577    -0.71   0.477    -.0712809    .0333459
                    hhi |   .0000428   .0000784     0.55   0.586    -.0001111    .0001966
                    age |   .0073661   .0031719     2.32   0.020     .0011414    .0135907
                  white |   .0428384   .1220716     0.35   0.726    -.1967165    .2823932
            SexismOrder |   -.046585    .099713    -0.47   0.640    -.2422631    .1490932
       nonwhite_placebo |  -.0653275   .1247554    -0.52   0.601    -.3101491    .1794941
                  _cons |   5.122429   .3495659    14.65   0.000     4.436436    5.808421
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .0117458     -.0213673      .0460813
        Direct Effect          |  .3994697      .2049557       .597461
        Total Effect           |  .4112155      .2505501      .5759955
        % of Tot Eff mediated  |  .0285296      .0203922      .0468801
------------------------------------------------------------------------------------

. 
. ***Doves        
. medeff (regress moderate conciliatory female democrat hostsexism benevsexism secordersexism hawkish female_responde
> nt political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 moderate con
> ciliatory female democrat hostsexism benevsexism hawkish female_respondent political_identfication education hhi ag
> e white SexismOrder nonwhite_placebo) if dove==1, mediate(moderate) treat(conciliatory) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       984
-------------+----------------------------------   F(15, 968)      =      5.06
       Model |  9.24422685        15   .61628179   Prob > F        =    0.0000
    Residual |  117.889919       968  .121787107   R-squared       =    0.0727
-------------+----------------------------------   Adj R-squared   =    0.0583
       Total |  127.134146       983  .129332804   Root MSE        =    .34898

-----------------------------------------------------------------------------------------
               moderate |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -.0964797   .0224011    -4.31   0.000      -.14044   -.0525194
                 female |  -.0027032   .0224199    -0.12   0.904    -.0467003    .0412939
               democrat |   -.062181   .0224651    -2.77   0.006    -.1062668   -.0180952
             hostsexism |  -.0384833   .0132081    -2.91   0.004    -.0644032   -.0125635
            benevsexism |  -.0090991   .0103563    -0.88   0.380    -.0294226    .0112243
         secordersexism |   .0020819   .0110705     0.19   0.851    -.0196431    .0238068
                hawkish |  -.0185457    .014292    -1.30   0.195    -.0465925    .0095011
      female_respondent |  -.0401181   .0230226    -1.74   0.082    -.0852981    .0050618
political_identfication |   -.005846   .0056411    -1.04   0.300    -.0169161    .0052241
              education |  -.0101636   .0059216    -1.72   0.086    -.0217842    .0014569
                    hhi |   .0000181   .0000162     1.12   0.265    -.0000137    .0000499
                    age |   .0031811   .0007113     4.47   0.000     .0017853    .0045769
                  white |   .0188137   .0276692     0.68   0.497    -.0354849    .0731123
            SexismOrder |   .0245906   .0225853     1.09   0.277    -.0197312    .0689124
       nonwhite_placebo |   .0038141   .0254103     0.15   0.881    -.0460516    .0536798
                  _cons |   .3536196   .0881362     4.01   0.000     .1806597    .5265796
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       984
-------------+----------------------------------   F(15, 968)      =     17.72
       Model |  513.109523        15  34.2073015   Prob > F        =    0.0000
    Residual |  1869.02056       968  1.93080636   R-squared       =    0.2154
-------------+----------------------------------   Adj R-squared   =    0.2032
       Total |  2382.13008       983  2.42332663   Root MSE        =    1.3895

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .8901174   .0900215     9.89   0.000     .7134577    1.066777
               moderate |  -.6734052   .1279744    -5.26   0.000    -.9245444    -.422266
                 female |   .0245252   .0892293     0.27   0.783    -.1505799    .1996303
               democrat |   .1510447   .0897892     1.68   0.093    -.0251592    .3272487
             hostsexism |   .0250431   .0520159     0.48   0.630    -.0770338      .12712
            benevsexism |  -.2737781   .0386335    -7.09   0.000    -.3495932   -.1979631
                hawkish |   .2118197   .0569284     3.72   0.000     .1001024     .323537
      female_respondent |   .1029446    .091624     1.12   0.261      -.07686    .2827492
political_identfication |   .0408997   .0224677     1.82   0.069    -.0031913    .0849906
              education |  -.0555077    .023574    -2.35   0.019    -.1017697   -.0092457
                    hhi |  -.0000719   .0000645    -1.11   0.265    -.0001985    .0000547
                    age |    .009359   .0028555     3.28   0.001     .0037552    .0149627
                  white |  -.1617724   .1098294    -1.47   0.141    -.3773035    .0537588
            SexismOrder |  -.0852379   .0899664    -0.95   0.344    -.2617895    .0913138
       nonwhite_placebo |   .2892521   .1009873     2.86   0.004     .0910728    .4874315
                  _cons |   2.402711   .3222925     7.46   0.000     1.770238    3.035183
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .0650789      .0278412       .109673
        Direct Effect          |  .8910269      .7154121      1.069781
        Total Effect           |  .9561058      .8118825       1.10298
        % of Tot Eff mediated  |  .0679721      .0590028       .080158
------------------------------------------------------------------------------------

. 
. ***** TRUSTWORTHINESS ***** 
. 
. ***Hawk
. medeff (regress trustworthy1 conciliatory female democrat hostsexism benevsexism secordersexism hawkish female_resp
> ondent political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 trustwor
> thy1 conciliatory female democrat hostsexism benevsexism hawkish female_respondent political_identfication educatio
> n hhi age white SexismOrder nonwhite_placebo) if hawk==1, mediate(trustworthy1) treat(conciliatory) sims(2000) seed
> (8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       986
-------------+----------------------------------   F(15, 970)      =      8.54
       Model |  290.957047        15  19.3971365   Prob > F        =    0.0000
    Residual |  2203.49326       970  2.27164253   R-squared       =    0.1166
-------------+----------------------------------   Adj R-squared   =    0.1030
       Total |   2494.4503       985  2.53243686   Root MSE        =    1.5072

-----------------------------------------------------------------------------------------
           trustworthy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -.1994284   .0967718    -2.06   0.040    -.3893345   -.0095222
                 female |  -.1348822   .0968255    -1.39   0.164    -.3248937    .0551293
               democrat |   .0921762   .0966754     0.95   0.341    -.0975408    .2818933
             hostsexism |   .0547783   .0557174     0.98   0.326    -.0545622    .1641188
            benevsexism |   .2175622   .0420417     5.17   0.000     .1350589    .3000654
         secordersexism |   .0620577   .0452978     1.37   0.171    -.0268353    .1509507
                hawkish |   .3334752   .0601209     5.55   0.000     .2154932    .4514572
      female_respondent |  -.3683491    .100511    -3.66   0.000    -.5655931   -.1711052
political_identfication |   .0425538   .0237138     1.79   0.073    -.0039824      .08909
              education |   .0035861   .0259098     0.14   0.890    -.0472596    .0544318
                    hhi |  -.0000528   .0000759    -0.70   0.487    -.0002017    .0000962
                    age |  -.0028229   .0030688    -0.92   0.358    -.0088451    .0031994
                  white |   .0375657   .1184383     0.32   0.751    -.1948591    .2699905
            SexismOrder |   .1010519   .0967015     1.04   0.296    -.0887163    .2908201
       nonwhite_placebo |  -.0907777   .1210421    -0.75   0.453    -.3283123    .1467569
                  _cons |   2.473477   .3649745     6.78   0.000     1.757246    3.189707
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       986
-------------+----------------------------------   F(15, 970)      =     73.52
       Model |  1468.16204        15  97.8774696   Prob > F        =    0.0000
    Residual |  1291.39171       970  1.33133166   R-squared       =    0.5320
-------------+----------------------------------   Adj R-squared   =    0.5248
       Total |  2759.55375       985  2.80157741   Root MSE        =    1.1538

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .2731297   .0741606     3.68   0.000      .127596    .4186634
           trustworthy1 |  -.7112607   .0245566   -28.96   0.000    -.7594508   -.6630706
                 female |   .0477957   .0741891     0.64   0.520     -.097794    .1933854
               democrat |   .1251842   .0740237     1.69   0.091    -.0200808    .2704492
             hostsexism |    -.07548   .0422996    -1.78   0.075    -.1584893    .0075293
            benevsexism |   .0124253   .0315946     0.39   0.694    -.0495763     .074427
                hawkish |  -.1960908   .0467408    -4.20   0.000    -.2878155    -.104366
      female_respondent |   .1363288   .0774742     1.76   0.079    -.0157075    .2883651
political_identfication |   .0139755   .0181713     0.77   0.442    -.0216841    .0496352
              education |   -.012325   .0197896    -0.62   0.534    -.0511604    .0265104
                    hhi |  -.0000186   .0000581    -0.32   0.749    -.0001326    .0000955
                    age |   .0041988   .0023492     1.79   0.074    -.0004113    .0088088
                  white |   .0807819   .0906313     0.89   0.373    -.0970742     .258638
            SexismOrder |   .0305566   .0740671     0.41   0.680    -.1147935    .1759068
       nonwhite_placebo |  -.1196925   .0926317    -1.29   0.197    -.3014741    .0620891
                  _cons |   6.806308   .2659447    25.59   0.000     6.284414    7.328201
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .1412276      .0044884      .2805811
        Direct Effect          |  .2738789      .1292057      .4211386
        Total Effect           |  .4151066      .3975916      .4264435
        % of Tot Eff mediated  |  .3393842      .3311755      .3552078
------------------------------------------------------------------------------------

. 
. ***Doves        
. medeff (regress trustworthy1 conciliatory female democrat hostsexism benevsexism secordersexism hawkish female_resp
> ondent political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 trustwor
> thy1 conciliatory female democrat hostsexism benevsexism hawkish female_respondent political_identfication educatio
> n hhi age white SexismOrder nonwhite_placebo) if dove==1, mediate(trustworthy1) treat(conciliatory) sims(2000) seed
> (8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       984
-------------+----------------------------------   F(15, 968)      =      8.25
       Model |  241.412123        15  16.0941415   Prob > F        =    0.0000
    Residual |  1887.88869       968  1.95029823   R-squared       =    0.1134
-------------+----------------------------------   Adj R-squared   =    0.0996
       Total |  2129.30081       983  2.16612494   Root MSE        =    1.3965

-----------------------------------------------------------------------------------------
           trustworthy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -.4501006   .0896436    -5.02   0.000    -.6260187   -.2741825
                 female |   .0427346   .0897186     0.48   0.634    -.1333309       .2188
               democrat |  -.1484016   .0898995    -1.65   0.099    -.3248219    .0280188
             hostsexism |   -.185213   .0528556    -3.50   0.000    -.2889376   -.0814883
            benevsexism |   .2821776   .0414434     6.81   0.000     .2008484    .3635069
         secordersexism |  -.0581768   .0443014    -1.31   0.189    -.1451147    .0287611
                hawkish |  -.1360974   .0571929    -2.38   0.018    -.2483337   -.0238611
      female_respondent |  -.1831915   .0921306    -1.99   0.047    -.3639902   -.0023927
political_identfication |  -.0025906   .0225741    -0.11   0.909    -.0468904    .0417092
              education |   .0291522   .0236966     1.23   0.219    -.0173505    .0756549
                    hhi |   .0000754   .0000648     1.16   0.245    -.0000518    .0002026
                    age |   .0022834   .0028463     0.80   0.423    -.0033022     .007869
                  white |  -.0359079   .1107254    -0.32   0.746    -.2531973    .1813816
            SexismOrder |    .111372   .0903807     1.23   0.218    -.0659927    .2887367
       nonwhite_placebo |  -.2290238   .1016858    -2.25   0.025    -.4285738   -.0294738
                  _cons |   5.471315   .3526988    15.51   0.000     4.779173    6.163458
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       984
-------------+----------------------------------   F(15, 968)      =     71.68
       Model |  1253.52831        15   83.568554   Prob > F        =    0.0000
    Residual |  1128.60177       968  1.16591092   R-squared       =    0.5262
-------------+----------------------------------   Adj R-squared   =    0.5189
       Total |  2382.13008       983  2.42332663   Root MSE        =    1.0798

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |     .66171   .0701995     9.43   0.000     .5239493    .7994707
           trustworthy1 |  -.6478925   .0248289   -26.09   0.000    -.6966172   -.5991678
                 female |   .0516483   .0693442     0.74   0.457    -.0844341    .1877307
               democrat |   .0981775   .0695927     1.41   0.159    -.0383924    .2347474
             hostsexism |  -.0608661   .0404633    -1.50   0.133     -.140272    .0185399
            benevsexism |  -.0976519   .0307122    -3.18   0.002    -.1579221   -.0373817
                hawkish |   .1377116   .0443235     3.11   0.002     .0507304    .2246927
      female_respondent |   .0165177   .0712186     0.23   0.817     -.123243    .1562784
political_identfication |   .0427094   .0174497     2.45   0.015     .0084659    .0769529
              education |  -.0309843   .0183038    -1.69   0.091     -.066904    .0049354
                    hhi |  -.0000369   .0000501    -0.74   0.461    -.0001353    .0000614
                    age |   .0088529   .0021973     4.03   0.000     .0045409    .0131649
                  white |  -.2056954   .0853326    -2.41   0.016    -.3731535   -.0382373
            SexismOrder |  -.0281257   .0699251    -0.40   0.688     -.165348    .1090966
       nonwhite_placebo |   .1327983   .0786945     1.69   0.092    -.0216331    .2872297
                  _cons |   5.579634   .2803787    19.90   0.000     5.029414    6.129854
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .2912728      .1714206      .4125745
        Direct Effect          |  .6624192      .5254734      .8018134
        Total Effect           |  .9536921      .9206308      .9812247
        % of Tot Eff mediated  |  .3050955      .2968462       .316384
------------------------------------------------------------------------------------

. 
. 
. ********************************************************************************
. *                        TABLE A-16: STUDY 2 GENDER OUT-PARTISAN MEDIATION                                 *
. ********************************************************************************
. 
. eststo clear

. 
. ***** COMPETENCE ***** 
. 
. ***Male
. medeff (regress beststrategy1 conciliatory hawk democrat hostsexism benevsexism secordersexism hawkish female_respo
> ndent political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 beststrat
> egy1 conciliatory hawk democrat hostsexism benevsexism hawkish female_respondent political_identfication education 
> hhi age white SexismOrder nonwhite_placebo) if male==1 & out_partisan==1, mediate(beststrategy1) treat(conciliatory
> ) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       411
-------------+----------------------------------   F(15, 395)      =      1.93
       Model |  85.7281082        15  5.71520721   Prob > F        =    0.0190
    Residual |  1168.11617       395  2.95725614   R-squared       =    0.0684
-------------+----------------------------------   Adj R-squared   =    0.0330
       Total |  1253.84428       410  3.05815679   Root MSE        =    1.7197

-----------------------------------------------------------------------------------------
          beststrategy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |  -.4416206   .1750634    -2.52   0.012    -.7857932    -.097448
                   hawk |  -.2515099   .1732873    -1.45   0.147    -.5921906    .0891708
               democrat |   .7145285   .5422648     1.32   0.188    -.3515575    1.780615
             hostsexism |    .005709   .0990926     0.06   0.954    -.1891058    .2005239
            benevsexism |   .2796972    .076115     3.67   0.000     .1300561    .4293383
         secordersexism |  -.1215598   .0814829    -1.49   0.137    -.2817541    .0386346
                hawkish |   .0406101   .1092489     0.37   0.710    -.1741719     .255392
      female_respondent |  -.1470631   .1818171    -0.81   0.419    -.5045134    .2103873
political_identfication |  -.1003558    .109953    -0.91   0.362    -.3165221    .1158106
              education |   .0197425   .0440768     0.45   0.654     -.066912    .1063971
                    hhi |  -.0000581   .0001218    -0.48   0.634    -.0002977    .0001814
                    age |  -.0033273   .0055973    -0.59   0.553    -.0143315    .0076769
                  white |  -.0005006   .2182243    -0.00   0.998    -.4295269    .4285257
            SexismOrder |  -.0685011   .1727863    -0.40   0.692    -.4081968    .2711946
       nonwhite_placebo |  -.1383381    .223521    -0.62   0.536    -.5777776    .3011015
                  _cons |   4.564422   .6792556     6.72   0.000     3.229013     5.89983
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       411
-------------+----------------------------------   F(15, 395)      =     50.25
       Model |  766.480636        15  51.0987091   Prob > F        =    0.0000
    Residual |  401.699412       395  1.01696054   R-squared       =    0.6561
-------------+----------------------------------   Adj R-squared   =    0.6431
       Total |  1168.18005       410  2.84921963   Root MSE        =    1.0084

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .2636511   .1034364     2.55   0.011     .0602964    .4670057
          beststrategy1 |  -.7388962   .0294231   -25.11   0.000    -.7967417   -.6810507
                   hawk |   .3074594   .1017956     3.02   0.003     .1073305    .5075883
               democrat |   .0063425   .3186179     0.02   0.984    -.6200564    .6327414
             hostsexism |  -.0472239   .0569047    -0.83   0.407     -.159098    .0646501
            benevsexism |  -.0881448   .0426079    -2.07   0.039    -.1719114   -.0043783
                hawkish |  -.0752082   .0640241    -1.17   0.241    -.2010789    .0506624
      female_respondent |   .0143843   .1061866     0.14   0.892    -.1943773    .2231458
political_identfication |   .0493889   .0645399     0.77   0.445    -.0774957    .1762736
              education |  -.0254875   .0257196    -0.99   0.322     -.076052    .0250769
                    hhi |  -.0000479   .0000715    -0.67   0.503    -.0001884    .0000925
                    age |   .0028626   .0032821     0.87   0.384    -.0035899    .0093152
                  white |  -.2967289   .1277061    -2.32   0.021    -.5477976   -.0456602
            SexismOrder |  -.0266228   .1013429    -0.26   0.793    -.2258618    .1726162
       nonwhite_placebo |  -.1905469   .1310987    -1.45   0.147    -.4482855    .0671916
                  _cons |   7.133356   .3873933    18.41   0.000     6.371745    7.894966
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |   .325488      .0671575      .5907254
        Direct Effect          |  .2646961      .0629114      .4700883
        Total Effect           |  .5901842      .5359176       .655696
        % of Tot Eff mediated  |  .5532992      .4964009      .6073472
------------------------------------------------------------------------------------

. 
. ***Female
. medeff (regress beststrategy1 conciliatory hawk democrat hostsexism benevsexism secordersexism hawkish female_respo
> ndent political_identfication education hhi age white SexismOrder nonwhite_placebo) (regress disapproval1 beststrat
> egy1 conciliatory hawk democrat hostsexism benevsexism hawkish female_respondent political_identfication education 
> hhi age white SexismOrder nonwhite_placebo) if female==1 & out_partisan==1, mediate(beststrategy1) treat(conciliato
> ry) sims(2000) seed(8675309)
Using 0 and 1 as treatment values

      Source |       SS           df       MS      Number of obs   =       428
-------------+----------------------------------   F(15, 412)      =      4.08
       Model |   174.70613        15  11.6470754   Prob > F        =    0.0000
    Residual |  1176.19107       412  2.85483268   R-squared       =    0.1293
-------------+----------------------------------   Adj R-squared   =    0.0976
       Total |   1350.8972       427  3.16369367   Root MSE        =    1.6896

-----------------------------------------------------------------------------------------
          beststrategy1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   -.830188   .1678182    -4.95   0.000    -1.160075   -.5003012
                   hawk |   -.293238   .1659312    -1.77   0.078    -.6194154    .0329394
               democrat |    -.43556   .5311404    -0.82   0.413    -1.479643    .6085233
             hostsexism |   .0176939   .0960607     0.18   0.854    -.1711363    .2065241
            benevsexism |   .3070395   .0729018     4.21   0.000     .1637336    .4503454
         secordersexism |  -.0415024   .0828657    -0.50   0.617    -.2043948    .1213899
                hawkish |  -.0585748   .1013512    -0.58   0.564    -.2578049    .1406552
      female_respondent |  -.2673094   .1728924    -1.55   0.123    -.6071706    .0725519
political_identfication |   .0543041   .1053723     0.52   0.607    -.1528304    .2614386
              education |   .0411926    .045746     0.90   0.368    -.0487322    .1311173
                    hhi |  -.0001769   .0001477    -1.20   0.232    -.0004672    .0001134
                    age |   -.006479   .0052805    -1.23   0.221    -.0168591    .0039012
                  white |  -.1348098    .217385    -0.62   0.536    -.5621319    .2925122
            SexismOrder |   .1187762   .1680677     0.71   0.480     -.211601    .4491534
       nonwhite_placebo |   .0864974   .1895323     0.46   0.648    -.2860735    .4590683
                  _cons |   4.569983    .685901     6.66   0.000     3.221681    5.918285
-----------------------------------------------------------------------------------------

      Source |       SS           df       MS      Number of obs   =       428
-------------+----------------------------------   F(15, 412)      =     63.56
       Model |  919.284782        15  61.2856522   Prob > F        =    0.0000
    Residual |  397.264283       412  .964233697   R-squared       =    0.6983
-------------+----------------------------------   Adj R-squared   =    0.6873
       Total |  1316.54907       427  3.08325308   Root MSE        =    .98195

-----------------------------------------------------------------------------------------
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
           conciliatory |   .2434871   .0994586     2.45   0.015     .0479775    .4389967
          beststrategy1 |  -.7804131   .0286233   -27.26   0.000    -.8366791   -.7241471
                   hawk |   .2718189   .0967964     2.81   0.005     .0815425    .4620952
               democrat |    .051165   .3081524     0.17   0.868     -.554582    .6569119
             hostsexism |   .0671196   .0555123     1.21   0.227    -.0420032    .1762423
            benevsexism |  -.0265805   .0414213    -0.64   0.521     -.108004     .054843
                hawkish |  -.0632412   .0588619    -1.07   0.283    -.1789484     .052466
      female_respondent |    .049133   .1005451     0.49   0.625    -.1485124    .2467784
political_identfication |   .0061678   .0611718     0.10   0.920    -.1140801    .1264156
              education |  -.0445632   .0265681    -1.68   0.094    -.0967892    .0076627
                    hhi |  -.0000279   .0000859    -0.33   0.745    -.0001967    .0001409
                    age |   .0028475   .0030644     0.93   0.353    -.0031763    .0088712
                  white |   .0511559   .1229415     0.42   0.678     -.190515    .2928268
            SexismOrder |  -.1081247   .0973422    -1.11   0.267     -.299474    .0832246
       nonwhite_placebo |   .1724847   .1101491     1.57   0.118    -.0440396    .3890091
                  _cons |   6.706509   .3904567    17.18   0.000     5.938973    7.474045
-----------------------------------------------------------------------------------------
The number of observations in the data is less than the number of simulations. Expanding the data to the number of si
> mulations
------------------------------------------------------------------------------------
        Effect                 |  Mean           [95% Conf. Interval]
-------------------------------+----------------------------------------------------
        ACME                   |  .6474755      .3738358      .9245606
        Direct Effect          |  .2444919      .0504671      .4419855
        Total Effect           |  .8919675        .81184      .9855343
        % of Tot Eff mediated  |  .7276698      .6569793      .7975408
------------------------------------------------------------------------------------

. 
. 
. ********************************************************************************
. *                                TABLE A-17: STUDY 2 HETEROGENEOUS EFFECTS                                         
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Republican Respondent
. eststo: reg disapproval1 1.femsq 1.femsq#republican_respondent 1.femconc 1.femconc#republican_respondent 1.malesq 1
> .malesq#republican_respondent 1.maleconc 1.maleconc#republican_respondent hawk democrat hostsexism benevsexism seco
> rdersexism hawkish female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, 
> robust noconst

Linear regression                               Number of obs     =      1,970
                                                F(22, 1948)       =     392.40
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8151
                                                Root MSE          =     1.5252

------------------------------------------------------------------------------------------------
                               |               Robust
                  disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
                       1.femsq |   3.539908   .3142325    11.27   0.000     2.923641    4.156176
                               |
   femsq#republican_respondent |
                          1 1  |  -.8358676   .1923613    -4.35   0.000    -1.213123   -.4586121
                               |
                     1.femconc |   3.887702   .3132053    12.41   0.000     3.273449    4.501955
                               |
 femconc#republican_respondent |
                          1 1  |   .0652849   .2050313     0.32   0.750    -.3368189    .4673886
                               |
                      1.malesq |   3.511359   .3142481    11.17   0.000     2.895061    4.127657
                               |
  malesq#republican_respondent |
                          1 1  |  -.9229565   .1811646    -5.09   0.000    -1.278253   -.5676597
                               |
                    1.maleconc |   3.803754   .3077154    12.36   0.000     3.200268     4.40724
                               |
maleconc#republican_respondent |
                          1 1  |   .0189686   .2007144     0.09   0.925     -.374669    .4126062
                               |
                          hawk |   .4309535   .0690962     6.24   0.000     .2954432    .5664638
                      democrat |   .1617961   .0691905     2.34   0.019      .026101    .2974913
                    hostsexism |  -.0456301   .0438815    -1.04   0.299    -.1316897    .0404296
                   benevsexism |    -.21268   .0320734    -6.63   0.000    -.2755818   -.1497781
                secordersexism |  -.0081039   .0356738    -0.23   0.820    -.0780668    .0618589
                       hawkish |  -.1106687   .0503792    -2.20   0.028    -.2094715   -.0118658
             female_respondent |   .2595628   .0727641     3.57   0.000      .116859    .4022666
       political_identfication |   .1024379   .0328334     3.12   0.002     .0380456    .1668303
                     education |  -.0409387   .0186318    -2.20   0.028    -.0774791   -.0043982
                           hhi |  -.0000201   .0000485    -0.41   0.679    -.0001152     .000075
                           age |   .0067286   .0022051     3.05   0.002     .0024039    .0110532
                         white |  -.0727168   .0845668    -0.86   0.390    -.2385677    .0931341
                   SexismOrder |  -.0675808   .0692148    -0.98   0.329    -.2033237    .0681621
              nonwhite_placebo |   .0734072   .0840495     0.87   0.383    -.0914293    .2382437
------------------------------------------------------------------------------------------------
(est1 stored)

. 
. *Gendered Peace Premium (Republican Respondent)
. lincom (1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.maleco
> nc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.republican_respondent + 1.femconc + 1.femconc#1.republican_respondent + 1.malesq +
       1.malesq#1.republican_respondent - 1.maleconc - 1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0146264   .2275921     0.06   0.949    -.4317232    .4609761
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Republican Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .055399   .1724333     0.32   0.748    -.2827742    .3935722
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.republican_respondent)-(1.femsq+1.femsq#1.republican_respondent)-(1.maleconc+1.malec
> onc#1.republican_respondent)+(1.malesq+1.malesq#1.republican_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.ma
> lesq))

 ( 1)  - 1.femsq#1.republican_respondent + 1.femconc#1.republican_respondent + 1.malesq#1.republican_respondent -
       1.maleconc#1.republican_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0407726    .285838    -0.14   0.887    -.6013531    .5198079
------------------------------------------------------------------------------

. 
. 
. ***Model 2: Hostile Sexism 
. eststo: reg disapproval1 1.femsq 1.femsq#hostsexismIQR 1.femconc 1.femconc#hostsexismIQR 1.malesq 1.malesq#hostsexi
> smIQR 1.maleconc 1.maleconc#hostsexismIQR hawk democrat republican_respondent benevsexism secordersexism hawkish fe
> male_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,324
                                                F(22, 1302)       =     249.95
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8070
                                                Root MSE          =     1.5714

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   3.140418   .3407715     9.22   0.000     2.471896    3.808939
                        |
    femsq#hostsexismIQR |
                   1 1  |  -.4126178   .1931234    -2.14   0.033    -.7914849   -.0337506
                        |
              1.femconc |   3.800206   .3454114    11.00   0.000     3.122582     4.47783
                        |
  femconc#hostsexismIQR |
                   1 1  |  -.1316167   .1981243    -0.66   0.507    -.5202946    .2570612
                        |
               1.malesq |   3.087777    .342504     9.02   0.000     2.415857    3.759697
                        |
   malesq#hostsexismIQR |
                   1 1  |  -.4046432   .1797983    -2.25   0.025    -.7573692   -.0519171
                        |
             1.maleconc |   3.678492    .330078    11.14   0.000     3.030949    4.326035
                        |
 maleconc#hostsexismIQR |
                   1 1  |  -.1533713   .1833863    -0.84   0.403    -.5131363    .2063937
                        |
                   hawk |   .4378577   .0874803     5.01   0.000       .26624    .6094754
               democrat |   .1858621    .087221     2.13   0.033     .0147531    .3569711
  republican_respondent |  -.4898455   .1956011    -2.50   0.012    -.8735734   -.1061176
            benevsexism |  -.2005803   .0374219    -5.36   0.000     -.273994   -.1271665
         secordersexism |  -.0135215   .0428595    -0.32   0.752    -.0976028    .0705598
                hawkish |  -.0888264   .0608721    -1.46   0.145    -.2082445    .0305917
      female_respondent |   .2139718   .0913864     2.34   0.019     .0346912    .3932524
political_identfication |   .1391344    .041584     3.35   0.001     .0575554    .2207134
              education |  -.0393339   .0235377    -1.67   0.095    -.0855098     .006842
                    hhi |   5.86e-06   .0000623     0.09   0.925    -.0001163     .000128
                    age |   .0081048   .0028572     2.84   0.005     .0024997      .01371
                  white |  -.0630277     .10835    -0.58   0.561    -.2755873    .1495319
            SexismOrder |  -.0964632   .0866508    -1.11   0.266    -.2664536    .0735273
       nonwhite_placebo |   .1872282   .1044814     1.79   0.073    -.0177421    .3921985
-----------------------------------------------------------------------------------------
(est2 stored)

. 
. *Gendered Peace Premium (Sexist Respondent)
. lincom (1.femconc+1.femconc#1.hostsexismIQR)-(1.femsq+1.femsq#1.hostsexismIQR)-(1.maleconc+1.maleconc#1.hostsexismI
> QR)+(1.malesq+1.malesq#1.hostsexismIQR)

 ( 1)  - 1.femsq - 1.femsq#1.hostsexismIQR + 1.femconc + 1.femconc#1.hostsexismIQR + 1.malesq +
       1.malesq#1.hostsexismIQR - 1.maleconc - 1.maleconc#1.hostsexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0988023   .2186929     0.45   0.651    -.3302267    .5278313
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Sexist Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |    .069073   .2848927     0.24   0.808     -.489826    .6279721
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hostsexismIQR)-(1.femsq+1.femsq#1.hostsexismIQR)-(1.maleconc+1.maleconc#1.hostsexism
> IQR)+(1.malesq+1.malesq#1.hostsexismIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hostsexismIQR + 1.femconc#1.hostsexismIQR + 1.malesq#1.hostsexismIQR - 1.maleconc#1.hostsexismIQR
       = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0297292    .360062     0.08   0.934    -.6766359    .7360943
------------------------------------------------------------------------------

. 
. 
. ***Model 3: Benevolent Sexism 
. eststo: reg disapproval1 1.femsq 1.femsq#benevsexismIQR 1.femconc 1.femconc#benevsexismIQR 1.malesq 1.malesq#benevs
> exismIQR 1.maleconc 1.maleconc#benevsexismIQR hawk democrat republican_respondent hostsexism secordersexism hawkish
>  female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,309
                                                F(22, 1287)       =     239.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8023
                                                Root MSE          =      1.569

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |     2.8433   .3721307     7.64   0.000     2.113251     3.57335
                        |
   femsq#benevsexismIQR |
                   1 1  |  -.3894498   .1774123    -2.20   0.028    -.7374988   -.0414009
                        |
              1.femconc |   3.743746   .3747017     9.99   0.000     3.008653    4.478839
                        |
 femconc#benevsexismIQR |
                   1 1  |  -.8837703   .1914476    -4.62   0.000    -1.259354   -.5081866
                        |
               1.malesq |   2.743327   .3618857     7.58   0.000     2.033377    3.453278
                        |
  malesq#benevsexismIQR |
                   1 1  |  -.4673554   .1603654    -2.91   0.004    -.7819617   -.1527491
                        |
             1.maleconc |   3.575354    .357112    10.01   0.000     2.874769     4.27594
                        |
maleconc#benevsexismIQR |
                   1 1  |  -.7694593   .1910864    -4.03   0.000    -1.144334   -.3945842
                        |
                   hawk |   .3741235   .0877878     4.26   0.000     .2019005    .5463464
               democrat |   .1545797   .0874349     1.77   0.077    -.0169508    .3261102
  republican_respondent |  -.4547374   .1932517    -2.35   0.019    -.8338603   -.0756144
             hostsexism |  -.0638278   .0535699    -1.19   0.234    -.1689218    .0412662
         secordersexism |  -.0092641   .0414471    -0.22   0.823    -.0905754    .0720473
                hawkish |  -.1031574   .0618075    -1.67   0.095     -.224412    .0180971
      female_respondent |   .2758403   .0928039     2.97   0.003     .0937769    .4579038
political_identfication |   .0995746   .0416949     2.39   0.017     .0177771     .181372
              education |  -.0402707   .0238748    -1.69   0.092    -.0871085    .0065671
                    hhi |  -.0000178   .0000632    -0.28   0.778    -.0001419    .0001062
                    age |   .0078999   .0029419     2.69   0.007     .0021285    .0136714
                  white |  -.1822736   .1111574    -1.64   0.101    -.4003433     .035796
            SexismOrder |  -.0501941   .0877049    -0.57   0.567    -.2222543    .1218662
       nonwhite_placebo |   .1480985   .1071721     1.38   0.167    -.0621528    .3583497
-----------------------------------------------------------------------------------------
(est3 stored)

. 
. *Gendered Peace Premium (Sexist Respondent)
. lincom (1.femconc+1.femconc#1.benevsexismIQR)-(1.femsq+1.femsq#1.benevsexismIQR)-(1.maleconc+1.maleconc#1.benevsexi
> smIQR)+(1.malesq+1.malesq#1.benevsexismIQR)

 ( 1)  - 1.femsq - 1.femsq#1.benevsexismIQR + 1.femconc + 1.femconc#1.benevsexismIQR + 1.malesq +
       1.malesq#1.benevsexismIQR - 1.maleconc - 1.maleconc#1.benevsexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.1237977   .2716777    -0.46   0.649    -.6567775    .4091821
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Sexist Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0684189   .2267347     0.30   0.763    -.3763913     .513229
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.benevsexismIQR)-(1.femsq+1.femsq#1.benevsexismIQR)-(1.maleconc+1.maleconc#1.benevsex
> ismIQR)+(1.malesq+1.malesq#1.benevsexismIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.benevsexismIQR + 1.femconc#1.benevsexismIQR + 1.malesq#1.benevsexismIQR -
       1.maleconc#1.benevsexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.1922166   .3534669    -0.54   0.587    -.8856511     .501218
------------------------------------------------------------------------------

. 
. 
. ***Model 4: Second-Order Sexism 
. eststo: reg disapproval1 1.femsq 1.femsq#secordersexismIQR 1.femconc 1.femconc#secordersexismIQR 1.malesq 1.malesq#
> secordersexismIQR 1.maleconc 1.maleconc#secordersexismIQR hawk democrat republican_respondent hostsexism benevsexis
> m hawkish female_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust no
> const

Linear regression                               Number of obs     =      1,189
                                                F(22, 1167)       =     202.01
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7910
                                                Root MSE          =     1.5904

--------------------------------------------------------------------------------------------
                           |               Robust
              disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                   1.femsq |   3.189696    .387388     8.23   0.000     2.429641    3.949751
                           |
   femsq#secordersexismIQR |
                      1 1  |   .2996191   .1864693     1.61   0.108    -.0662334    .6654717
                           |
                 1.femconc |   4.043547   .3952288    10.23   0.000     3.268109    4.818986
                           |
 femconc#secordersexismIQR |
                      1 1  |  -.1418774    .206938    -0.69   0.493    -.5478896    .2641347
                           |
                  1.malesq |   3.426492   .3881637     8.83   0.000     2.664915    4.188069
                           |
  malesq#secordersexismIQR |
                      1 1  |  -.2933411   .1779713    -1.65   0.100    -.6425207    .0558385
                           |
                1.maleconc |   3.856866   .3838177    10.05   0.000     3.103816    4.609916
                           |
maleconc#secordersexismIQR |
                      1 1  |   .0178175   .2053087     0.09   0.931    -.3849981     .420633
                           |
                      hawk |   .4775218   .0930915     5.13   0.000     .2948764    .6601672
                  democrat |   .1101156   .0934645     1.18   0.239    -.0732616    .2934929
     republican_respondent |  -.2934461   .2144448    -1.37   0.171    -.7141865    .1272944
                hostsexism |  -.0649672   .0592783    -1.10   0.273    -.1812711    .0513367
               benevsexism |  -.2074021   .0393908    -5.27   0.000    -.2846867   -.1301174
                   hawkish |  -.1295243   .0642168    -2.02   0.044    -.2555176   -.0035311
         female_respondent |   .3379004   .1004241     3.36   0.001     .1408685    .5349323
   political_identfication |   .0657642   .0447589     1.47   0.142    -.0220528    .1535812
                 education |  -.0554177   .0247585    -2.24   0.025    -.1039938   -.0068416
                       hhi |  -.0000549   .0000617    -0.89   0.374     -.000176    .0000661
                       age |   .0074724   .0031403     2.38   0.017     .0013111    .0136337
                     white |  -.0196182   .1151201    -0.17   0.865    -.2454838    .2062474
               SexismOrder |   .0171444   .0935671     0.18   0.855    -.1664341    .2007229
          nonwhite_placebo |    .179819   .1104143     1.63   0.104    -.0368138    .3964518
--------------------------------------------------------------------------------------------
(est4 stored)

. 
. *Gendered Peace Premium (Sexist Respondent)
. lincom (1.femconc+1.femconc#1.secordersexismIQR)-(1.femsq+1.femsq#1.secordersexismIQR)-(1.maleconc+1.maleconc#1.sec
> ordersexismIQR)+(1.malesq+1.malesq#1.secordersexismIQR)

 ( 1)  - 1.femsq - 1.femsq#1.secordersexismIQR + 1.femconc + 1.femconc#1.secordersexismIQR + 1.malesq +
       1.malesq#1.secordersexismIQR - 1.maleconc - 1.maleconc#1.secordersexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.3291776   .2431377    -1.35   0.176    -.8062136    .1478583
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Sexist Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .4234775   .2829848     1.50   0.135    -.1317384    .9786934
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.secordersexismIQR)-(1.femsq+1.femsq#1.secordersexismIQR)-(1.maleconc+1.maleconc#1.se
> cordersexismIQR)+(1.malesq+1.malesq#1.secordersexismIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.secordersexismIQR + 1.femconc#1.secordersexismIQR + 1.malesq#1.secordersexismIQR -
       1.maleconc#1.secordersexismIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.7526551   .3730509    -2.02   0.044    -1.484581   -.0207296
------------------------------------------------------------------------------

. 
. 
. ***Model 5: Militant Assertiveness 
. eststo: reg disapproval1 1.femsq 1.femsq#hawkishIQR 1.femconc 1.femconc#hawkishIQR 1.malesq 1.malesq#hawkishIQR 1.m
> aleconc 1.maleconc#hawkishIQR hawk democrat republican_respondent hostsexism benevsexism secordersexism female_resp
> ondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,321
                                                F(22, 1299)       =     240.81
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8042
                                                Root MSE          =     1.5965

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |   3.498406    .368715     9.49   0.000     2.775064    4.221748
                        |
       femsq#hawkishIQR |
                   1 1  |  -.9712254   .1794765    -5.41   0.000    -1.323321   -.6191298
                        |
              1.femconc |   3.407776    .378632     9.00   0.000     2.664979    4.150574
                        |
     femconc#hawkishIQR |
                   1 1  |   .7598059   .2002252     3.79   0.000     .3670057    1.152606
                        |
               1.malesq |   3.312329   .3717604     8.91   0.000     2.583012    4.041645
                        |
      malesq#hawkishIQR |
                   1 1  |  -.9755729   .1578838    -6.18   0.000    -1.285308   -.6658377
                        |
             1.maleconc |   3.384908   .3636258     9.31   0.000      2.67155    4.098266
                        |
    maleconc#hawkishIQR |
                   1 1  |   .4563178   .1915393     2.38   0.017     .0805576     .832078
                        |
                   hawk |   .5249628   .0885522     5.93   0.000     .3512419    .6986837
               democrat |   .1586576   .0885969     1.79   0.074    -.0151511    .3324664
  republican_respondent |  -.2799322    .193496    -1.45   0.148    -.6595311    .0996668
             hostsexism |  -.0437924   .0524878    -0.83   0.404    -.1467626    .0591778
            benevsexism |  -.1801067   .0387173    -4.65   0.000     -.256062   -.1041515
         secordersexism |  -.0064543   .0441318    -0.15   0.884    -.0930318    .0801231
      female_respondent |   .2781034   .0931097     2.99   0.003     .0954415    .4607653
political_identfication |   .0821914   .0421374     1.95   0.051    -.0004735    .1648562
              education |  -.0426696   .0236957    -1.80   0.072    -.0891555    .0038164
                    hhi |  -.0000188   .0000634    -0.30   0.767    -.0001432    .0001057
                    age |   .0054011   .0029009     1.86   0.063    -.0002898     .011092
                  white |  -.1402515   .1094441    -1.28   0.200     -.354958     .074455
            SexismOrder |  -.0565965   .0894259    -0.63   0.527    -.2320316    .1188385
       nonwhite_placebo |    .014513   .1081637     0.13   0.893    -.1976817    .2267077
-----------------------------------------------------------------------------------------
(est5 stored)

. 
. *Gendered Peace Premium (Hawkish Respondent)
. lincom (1.femconc+1.femconc#1.hawkishIQR)-(1.femsq+1.femsq#1.hawkishIQR)-(1.maleconc+1.maleconc#1.hawkishIQR)+(1.ma
> lesq+1.malesq#1.hawkishIQR)

 ( 1)  - 1.femsq - 1.femsq#1.hawkishIQR + 1.femconc + 1.femconc#1.hawkishIQR + 1.malesq + 1.malesq#1.hawkishIQR -
       1.maleconc - 1.maleconc#1.hawkishIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1359322   .2484036     0.55   0.584    -.3513839    .6232483
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Non-Hawkish Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.1632084   .2523679    -0.65   0.518    -.6583017     .331885
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.hawkishIQR)-(1.femsq+1.femsq#1.hawkishIQR)-(1.maleconc+1.maleconc#1.hawkishIQR)+(1.m
> alesq+1.malesq#1.hawkishIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.hawkishIQR + 1.femconc#1.hawkishIQR + 1.malesq#1.hawkishIQR - 1.maleconc#1.hawkishIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .2991406    .353658     0.85   0.398    -.3946628     .992944
------------------------------------------------------------------------------

. 
. 
. ***Model 6: Education 
. eststo: reg disapproval1 1.femsq 1.femsq#educationIQR 1.femconc 1.femconc#educationIQR 1.malesq 1.malesq#educationI
> QR 1.maleconc 1.maleconc#educationIQR hawk democrat republican_respondent hostsexism benevsexism secordersexism haw
> kish female_respondent political_identfication hhi age white SexismOrder nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,415
                                                F(22, 1393)       =     267.71
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8050
                                                Root MSE          =     1.5389

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
                1.femsq |    3.63567   .3764168     9.66   0.000     2.897265    4.374075
                        |
     femsq#educationIQR |
                   1 1  |  -.4309906   .1770265    -2.43   0.015     -.778258   -.0837232
                        |
              1.femconc |   3.942329    .375764    10.49   0.000     3.205204    4.679453
                        |
   femconc#educationIQR |
                   1 1  |   .0764692   .1856225     0.41   0.680    -.2876605    .4405989
                        |
               1.malesq |   3.369874   .3755459     8.97   0.000     2.633177     4.10657
                        |
    malesq#educationIQR |
                   1 1  |  -.0823808   .1579809    -0.52   0.602    -.3922869    .2275254
                        |
             1.maleconc |   4.037132   .3638927    11.09   0.000     3.323295    4.750969
                        |
  maleconc#educationIQR |
                   1 1  |  -.0862374   .1716352    -0.50   0.615    -.4229289     .250454
                        |
                   hawk |   .4237843   .0822596     5.15   0.000     .2624183    .5851504
               democrat |   .0484718   .0825618     0.59   0.557     -.113487    .2104306
  republican_respondent |  -.5538158   .1817547    -3.05   0.002    -.9103584   -.1972733
             hostsexism |  -.0589465   .0555594    -1.06   0.289    -.1679355    .0500426
            benevsexism |  -.2088904   .0368527    -5.67   0.000    -.2811832   -.1365976
         secordersexism |   -.048466   .0419233    -1.16   0.248    -.1307057    .0337736
                hawkish |  -.1409678   .0613443    -2.30   0.022     -.261305   -.0206306
      female_respondent |   .3086393    .087263     3.54   0.000     .1374583    .4798203
political_identfication |   .1231968   .0391152     3.15   0.002     .0464657    .1999279
                    hhi |   .0000297   .0000507     0.59   0.558    -.0000698    .0001292
                    age |   .0069074    .002719     2.54   0.011     .0015735    .0122412
                  white |    .016137    .103401     0.16   0.876    -.1867014    .2189754
            SexismOrder |  -.0998368   .0827245    -1.21   0.228    -.2621148    .0624411
       nonwhite_placebo |   .1330245   .1031612     1.29   0.197    -.0693436    .3353925
-----------------------------------------------------------------------------------------
(est6 stored)

. 
. *Gendered Peace Premium (Educated Respondent)
. lincom (1.femconc+1.femconc#1.educationIQR)-(1.femsq+1.femsq#1.educationIQR)-(1.maleconc+1.maleconc#1.educationIQR)
> +(1.malesq+1.malesq#1.educationIQR)

 ( 1)  - 1.femsq - 1.femsq#1.educationIQR + 1.femconc + 1.femconc#1.educationIQR + 1.malesq + 1.malesq#1.educationIQR
       - 1.maleconc - 1.maleconc#1.educationIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1507172   .2049256     0.74   0.462    -.2512789    .5527134
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Uneducated Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.3605993   .2727511    -1.32   0.186    -.8956464    .1744479
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.educationIQR)-(1.femsq+1.femsq#1.educationIQR)-(1.maleconc+1.maleconc#1.educationIQR
> )+(1.malesq+1.malesq#1.educationIQR))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.educationIQR + 1.femconc#1.educationIQR + 1.malesq#1.educationIQR - 1.maleconc#1.educationIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .5113165   .3403066     1.50   0.133    -.1562523    1.178885
------------------------------------------------------------------------------

. 
. 
. ***Model 7: Female Respondents
. eststo: reg disapproval1 1.femsq 1.femsq#female_respondent 1.femconc 1.femconc#female_respondent 1.malesq 1.malesq#
> female_respondent 1.maleconc 1.maleconc#female_respondent hawk democrat republican_respondent hostsexism benevsexis
> m secordersexism hawkish political_identfication education hhi age white SexismOrder nonwhite_placebo, robust nocon
> st

Linear regression                               Number of obs     =      1,970
                                                F(22, 1948)       =     384.87
                                                Prob > F          =     0.0000
                                                R-squared         =     0.8112
                                                Root MSE          =     1.5414

--------------------------------------------------------------------------------------------
                           |               Robust
              disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                   1.femsq |   3.200942   .3173511    10.09   0.000     2.578559    3.823326
                           |
   femsq#female_respondent |
                      1 1  |   .3887472   .1369831     2.84   0.005     .1200983    .6573961
                           |
                 1.femconc |   3.955449   .3250351    12.17   0.000     3.317995    4.592902
                           |
 femconc#female_respondent |
                      1 1  |   .2853216   .1506824     1.89   0.058     -.010194    .5808372
                           |
                  1.malesq |   3.255069   .3203441    10.16   0.000     2.626816    3.883322
                           |
  malesq#female_respondent |
                      1 1  |   .1390923   .1282943     1.08   0.278    -.1125162    .3907007
                           |
                1.maleconc |   3.883001   .3196772    12.15   0.000     3.256056    4.509947
                           |
maleconc#female_respondent |
                      1 1  |   .2434674   .1476577     1.65   0.099    -.0461162     .533051
                           |
                      hawk |   .4279789   .0697857     6.13   0.000     .2911163    .5648415
                  democrat |   .1552191   .0698455     2.22   0.026     .0182394    .2921989
     republican_respondent |  -.4318674   .1527916    -2.83   0.005    -.7315197   -.1322151
                hostsexism |  -.0430699    .044987    -0.96   0.338    -.1312976    .0451579
               benevsexism |  -.2110034   .0325323    -6.49   0.000    -.2748052   -.1472016
            secordersexism |  -.0015837     .03626    -0.04   0.965    -.0726962    .0695288
                   hawkish |  -.0994665   .0512031    -1.94   0.052    -.1998851     .000952
   political_identfication |   .1041725    .033396     3.12   0.002     .0386767    .1696682
                 education |  -.0386322   .0187503    -2.06   0.039    -.0754049   -.0018596
                       hhi |  -.0000247   .0000494    -0.50   0.616    -.0001215    .0000721
                       age |   .0069013   .0022299     3.09   0.002     .0025279    .0112746
                     white |  -.0628817   .0853511    -0.74   0.461    -.2302708    .1045075
               SexismOrder |  -.0483266   .0700017    -0.69   0.490    -.1856127    .0889595
          nonwhite_placebo |   .0877058   .0850639     1.03   0.303      -.07912    .2545316
--------------------------------------------------------------------------------------------
(est7 stored)

. 
. *Gendered Peace Premium (Female Respondent)
. lincom (1.femconc+1.femconc#1.female_respondent)-(1.femsq+1.femsq#1.female_respondent)-(1.maleconc+1.maleconc#1.fem
> ale_respondent)+(1.malesq+1.malesq#1.female_respondent)

 ( 1)  - 1.femsq - 1.femsq#1.female_respondent + 1.femconc + 1.femconc#1.female_respondent + 1.malesq +
       1.malesq#1.female_respondent - 1.maleconc - 1.maleconc#1.female_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.0812266   .1909382    -0.43   0.671    -.4556913    .2932381
------------------------------------------------------------------------------

. 
. *Gendered Peace Premium (Male Respondent)
. lincom (1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq)

 ( 1)  - 1.femsq + 1.femconc + 1.malesq - 1.maleconc = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .1265741   .2022705     0.63   0.532    -.2701152    .5232634
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.femconc+1.femconc#1.female_respondent)-(1.femsq+1.femsq#1.female_respondent)-(1.maleconc+1.maleconc#1.fe
> male_respondent)+(1.malesq+1.malesq#1.female_respondent))-((1.femconc)-(1.femsq)-(1.maleconc)+(1.malesq))

 ( 1)  - 1.femsq#1.female_respondent + 1.femconc#1.female_respondent + 1.malesq#1.female_respondent -
       1.maleconc#1.female_respondent = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -.2078007   .2778953    -0.75   0.455     -.752804    .3372026
------------------------------------------------------------------------------

. 
. ********************************************************************************
. *                                        TABLE A-18: STUDY 2 OTHER HETEROGENEITY                                   
> *
. ********************************************************************************
. 
. eststo clear

. 
. ***Model 1: Sexists and Women Leaders
. 
. eststo: regress disapproval1 i.female##c.hostsexism conciliatory democrat hawk benevsexism secordersexism hawkish f
> emale_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =      1,970
                                                F(17, 1952)       =      16.25
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1102
                                                Root MSE          =     1.5433

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
               1.female |   .0420445   .2414039     0.17   0.862     -.431392    .5154809
             hostsexism |  -.0552732   .0582893    -0.95   0.343    -.1695889    .0590425
                        |
    female#c.hostsexism |
                     1  |   .0141912   .0773661     0.18   0.854    -.1375376      .16592
                        |
           conciliatory |   .6878956   .0694645     9.90   0.000     .5516631    .8241281
               democrat |   .1476759   .0701399     2.11   0.035      .010119    .2852328
                   hawk |   .4278854   .0699452     6.12   0.000     .2907102    .5650605
            benevsexism |  -.2143309   .0325901    -6.58   0.000    -.2782459   -.1504159
         secordersexism |   -.002051     .03624    -0.06   0.955    -.0731243    .0690222
                hawkish |  -.1097119   .0510256    -2.15   0.032    -.2097822   -.0096415
      female_respondent |   .2624821   .0737247     3.56   0.000     .1178947    .4070695
political_identfication |   .0249392   .0177619     1.40   0.160    -.0098952    .0597736
              education |  -.0433754   .0187184    -2.32   0.021    -.0800855   -.0066654
                    hhi |  -.0000328    .000049    -0.67   0.504    -.0001289    .0000634
                    age |   .0063502   .0022307     2.85   0.004     .0019754     .010725
                  white |  -.0701472   .0848833    -0.83   0.409    -.2366187    .0963243
            SexismOrder |  -.0476187   .0700101    -0.68   0.496    -.1849212    .0896838
       nonwhite_placebo |   .0849911   .0853092     1.00   0.319    -.0823157    .2522978
                  _cons |   3.459707   .3166163    10.93   0.000     2.838766    4.080649
-----------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. ***Model 2: Hawks and Conciliation
. 
. eststo: regress disapproval1 i.conciliatory##c.hawkish female democrat hawk hostsexism benevsexism secordersexism f
> emale_respondent political_identfication education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =      1,970
                                                F(17, 1952)       =      22.84
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1635
                                                Root MSE          =     1.4964

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
         1.conciliatory |  -2.026179   .2897139    -6.99   0.000     -2.59436   -1.457998
                hawkish |  -.5320839   .0620467    -8.58   0.000    -.6537687   -.4103992
                        |
 conciliatory#c.hawkish |
                     1  |   .8642142   .0894786     9.66   0.000     .6887306    1.039698
                        |
                 female |   .1063211   .0674481     1.58   0.115    -.0259566    .2385989
               democrat |   .1390146   .0677683     2.05   0.040     .0061088    .2719204
                   hawk |   .4575248   .0676149     6.77   0.000     .3249198    .5901298
             hostsexism |   -.047311   .0429434    -1.10   0.271    -.1315308    .0369087
            benevsexism |  -.2186598   .0312988    -6.99   0.000    -.2800425   -.1572772
         secordersexism |  -.0047615   .0352771    -0.13   0.893    -.0739461    .0644232
      female_respondent |   .2681312   .0714393     3.75   0.000     .1280259    .4082366
political_identfication |   .0210768   .0175464     1.20   0.230    -.0133348    .0554885
              education |  -.0442967   .0181159    -2.45   0.015    -.0798252   -.0087682
                    hhi |  -.0000341   .0000488    -0.70   0.485    -.0001299    .0000617
                    age |    .006103   .0021688     2.81   0.005     .0018495    .0103564
                  white |  -.1445029   .0827824    -1.75   0.081    -.3068541    .0178483
            SexismOrder |  -.0388252    .067951    -0.57   0.568    -.1720893    .0944389
       nonwhite_placebo |   .0934728   .0819337     1.14   0.254     -.067214    .2541595
                  _cons |   4.843245   .3102603    15.61   0.000     4.234769    5.451721
-----------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. ***Model 3: Republicans and Conciliation
. 
. eststo: regress disapproval1 i.conciliatory##c.political_identfication female democrat hawk hostsexism benevsexism 
> secordersexism hawkish female_respondent education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =      1,970
                                                F(17, 1952)       =      18.49
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1241
                                                Root MSE          =     1.5313

--------------------------------------------------------------------------------------------------------
                                       |               Robust
                          disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------------------------------+----------------------------------------------------------------
                        1.conciliatory |   .0439651   .1356064     0.32   0.746    -.2219835    .3099137
               political_identfication |    -.05846   .0222645    -2.63   0.009    -.1021248   -.0147952
                                       |
conciliatory#c.political_identfication |
                                    1  |    .166341   .0308568     5.39   0.000     .1058252    .2268569
                                       |
                                female |    .083561   .0691015     1.21   0.227    -.0519595    .2190814
                              democrat |   .1542462    .069483     2.22   0.027     .0179775    .2905149
                                  hawk |   .4331327   .0693576     6.24   0.000     .2971099    .5691555
                            hostsexism |  -.0448111   .0440049    -1.02   0.309    -.1311126    .0414903
                           benevsexism |  -.2118287   .0321675    -6.59   0.000     -.274915   -.1487423
                        secordersexism |  -.0062851   .0357382    -0.18   0.860    -.0763742    .0638039
                               hawkish |  -.1178244   .0504949    -2.33   0.020    -.2168541   -.0187947
                     female_respondent |   .2556592    .073057     3.50   0.000     .1123812    .3989372
                             education |  -.0476206   .0185673    -2.56   0.010    -.0840345   -.0112067
                                   hhi |  -.0000312   .0000483    -0.65   0.519     -.000126    .0000636
                                   age |   .0062574   .0022056     2.84   0.005     .0019318     .010583
                                 white |  -.0807675   .0841779    -0.96   0.337    -.2458554    .0843205
                           SexismOrder |   -.069176   .0694142    -1.00   0.319    -.2053097    .0669577
                      nonwhite_placebo |   .0678552   .0845053     0.80   0.422    -.0978748    .2335852
                                 _cons |   3.829838    .297764    12.86   0.000     3.245869    4.413806
--------------------------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. ***Model 4: Women and Women Leaders
. 
. eststo: regress disapproval1 i.female##i.female_respondent conciliatory democrat hawk hostsexism benevsexism secord
> ersexism hawkish political_identfication education hhi age white SexismOrder nonwhite_placebo, robust

Linear regression                               Number of obs     =      1,970
                                                F(17, 1952)       =      16.24
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1107
                                                Root MSE          =     1.5429

------------------------------------------------------------------------------------------
                         |               Robust
            disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
                1.female |   .0113464   .1007228     0.11   0.910    -.1861892     .208882
     1.female_respondent |   .1899775   .0995609     1.91   0.057    -.0052793    .3852343
                         |
female#female_respondent |
                    1 1  |   .1423193   .1390548     1.02   0.306    -.1303923    .4150308
                         |
            conciliatory |   .6876848    .069441     9.90   0.000     .5514985    .8238711
                democrat |   .1478116   .0699752     2.11   0.035     .0105776    .2850456
                    hawk |   .4275338    .069893     6.12   0.000     .2904611    .5646064
              hostsexism |  -.0473939   .0450385    -1.05   0.293    -.1357224    .0409346
             benevsexism |  -.2143593   .0325363    -6.59   0.000    -.2781689   -.1505497
          secordersexism |  -.0016946   .0362275    -0.05   0.963    -.0727432     .069354
                 hawkish |  -.1103172   .0510709    -2.16   0.031    -.2104763   -.0101581
 political_identfication |   .0252604   .0177728     1.42   0.155    -.0095953    .0601161
               education |  -.0437029   .0186967    -2.34   0.020    -.0803704   -.0070354
                     hhi |  -.0000327   .0000489    -0.67   0.503    -.0001286    .0000632
                     age |   .0064688   .0022277     2.90   0.004     .0020998    .0108378
                   white |  -.0757623   .0848303    -0.89   0.372    -.2421298    .0906052
             SexismOrder |   -.046492   .0699831    -0.66   0.507    -.1837414    .0907573
        nonwhite_placebo |   .0838162   .0851453     0.98   0.325     -.083169    .2508014
                   _cons |   3.472473   .3000369    11.57   0.000     2.884047    4.060899
------------------------------------------------------------------------------------------
(est1 stored)

. eststo clear

. 
. ***Model 5: Hawks and Hawks Advantage
. 
. eststo: regress disapproval1 i.dovesq##i.hawkishIQR i.doveconc##i.hawkishIQR i.hawksq##i.hawkishIQR female democrat
>  hostsexism benevsexism secordersexism female_respondent political_identfication education hhi age white SexismOrde
> r nonwhite_placebo, robust noconst

Linear regression                               Number of obs     =      1,321
                                                F(20, 1301)       =     243.84
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7957
                                                Root MSE          =     1.6295

-----------------------------------------------------------------------------------------
                        |               Robust
           disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------+----------------------------------------------------------------
               1.dovesq |  -.6752204   .1656763    -4.08   0.000    -1.000242   -.3501984
           1.hawkishIQR |   .1759426   .2002134     0.88   0.380    -.2168338     .568719
                        |
      dovesq#hawkishIQR |
                   1 1  |  -.5865761   .2400838    -2.44   0.015     -1.05757   -.1155824
                        |
             1.doveconc |  -.2755304   .1774604    -1.55   0.121    -.6236703    .0726094
                        |
    doveconc#hawkishIQR |
                   1 1  |   .6788707   .2675153     2.54   0.011     .1540622    1.203679
                        |
               1.hawksq |   1.112502   .2053036     5.42   0.000     .7097394    1.515264
                        |
      hawksq#hawkishIQR |
                   1 1  |  -2.396008   .2702723    -8.87   0.000    -2.926225   -1.865791
                        |
                 female |   .3164339   .0891204     3.55   0.000     .1415985    .4912693
               democrat |   .2161167   .0893561     2.42   0.016     .0408188    .3914145
             hostsexism |   .2734834   .0441661     6.19   0.000     .1868389    .3601279
            benevsexism |  -.0448331    .038175    -1.17   0.240    -.1197245    .0300582
         secordersexism |   .1949189   .0402009     4.85   0.000     .1160531    .2737846
      female_respondent |   .5680985   .0902552     6.29   0.000     .3910369    .7451601
political_identfication |   .0416677   .0232679     1.79   0.074    -.0039791    .0873145
              education |   .0569937   .0227032     2.51   0.012     .0124548    .1015327
                    hhi |  -.0001385   .0000655    -2.11   0.035    -.0002671   -9.94e-06
                    age |   .0171965   .0027655     6.22   0.000     .0117712    .0226218
                  white |  -.0813369   .1121221    -0.73   0.468    -.3012969     .138623
            SexismOrder |   .1374976    .089056     1.54   0.123    -.0372115    .3122066
       nonwhite_placebo |   .1760548   .1081868     1.63   0.104    -.0361849    .3882945
-----------------------------------------------------------------------------------------
(est1 stored)

. 
. *Dispositional Peace Premium (High Militant Assertiveness)
. lincom (1.doveconc+1.doveconc#1.hawkishIQR)-(1.dovesq+1.dovesq#1.hawkishIQR)+(1.hawksq+1.hawksq#1.hawkishIQR)

 ( 1)  - 1.dovesq - 1.dovesq#1.hawkishIQR + 1.doveconc + 1.doveconc#1.hawkishIQR + 1.hawksq + 1.hawksq#1.hawkishIQR =
       0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .3816307   .2487022     1.53   0.125    -.1062705    .8695319
------------------------------------------------------------------------------

. 
. *Dispositional Peace Premium (Low Militant Assertiveness)
. lincom 1.doveconc-1.dovesq+1.hawksq     

 ( 1)  - 1.dovesq + 1.doveconc + 1.hawksq = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   1.512192   .2586607     5.85   0.000     1.004754    2.019629
------------------------------------------------------------------------------

. 
. *Difference 
. lincom ((1.doveconc+1.doveconc#1.hawkishIQR)-(1.dovesq+1.dovesq#1.hawkishIQR)+(1.hawksq+1.hawksq#1.hawkishIQR)) - (
> (1.doveconc-1.dovesq+1.hawksq))

 ( 1)  - 1.dovesq#1.hawkishIQR + 1.doveconc#1.hawkishIQR + 1.hawksq#1.hawkishIQR = 0

------------------------------------------------------------------------------
disapproval1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |  -1.130561   .3595513    -3.14   0.002    -1.835925   -.4251972
------------------------------------------------------------------------------

. 
. eststo clear

. 
. 
. clear

. 
. ********************************************************************************
. 
. clear all

. 
. log off
      name:  <unnamed>
       log:  /Users/cb2257/Desktop/ISQ Replication/isq_blair_schwartz.log
  log type:  text
 paused on:  11 Oct 2023, 23:53:28
---------------------------------------------------------------------------------------------------------------------
